Pluralsight Path. Building Deep Learning Solutions with PyTorch (2020)

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Pluralsight Path. Building Deep Learning Solutions with PyTorch (2020)

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文件列表

  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/exercise.7z 164.3 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/7. Running Distributed Training Using the PyTorch Estimator.mp4 26.2 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/07. Distributed Training in PyTorch Using the Horovod Framework.mp4 23.8 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/12. Exploring Pre-trained Models in PyTorch.mp4 22.1 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/13. Demo - The Train Helper Function.mp4 21.3 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/09. Training the Sequence-2-Sequence Model Using Teacher Forcing.mp4 21.0 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/07. Installing PyTorch with CPU Support Using Conda.mp4 20.1 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/06. Using Torchtext to Process Text Data.mp4 19.7 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/15. Instantiating a Deep Learning VM.mp4 19.5 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/2. Persisting and Loading PyTorch Models/10. Exporting a Model to ONNX and Loading in Caffe2.mp4 19.2 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/7. Demo - Defining the RNN.mp4 19.1 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/12. Demo - Building and Training Custom Neural Networks for Classification.mp4 19.1 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/08. Prototyping a PyTorch Model on SageMaker Notebooks.mp4 19.1 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/11. Distributed Training in PyTorch.mp4 18.6 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/07. Data Cleaning and Preparation.mp4 18.5 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/07. Creating a SageMaker Notebook Instance.mp4 18.2 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/4. Introducing Convolutional Neural Networks/7. Applying Convolutional and Pooling Layers.mp4 18.1 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/08. Instantiating the PyTorch Estimator for Distributed Training.mp4 18.1 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/7. Creating and Using a Clipper Cluster for Prediction.mp4 17.9 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/4. Creating PyTorch Solutions on the Google Cloud Platform/3. Setting up a Cloud Datalab VM.mp4 17.7 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/09. Demo - Building and Training a Regression Model.mp4 17.5 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/2. Persisting and Loading PyTorch Models/06. Saving and Loading Models Using torch.save().mp4 17.4 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/exercise.7z 17.3 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/04. Generating Analogies Using GloVe Embeddings.mp4 17.3 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/8. Demo - Training the RNN and Generating Names.mp4 17.2 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/4. Performing Multi-class Text Classification Using Characters/5. Designing an RNN for Multiclass Text Classification.mp4 17.1 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/12. Using PyTorch Estimators for Distributed Training.mp4 17.0 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/03. Prototyping PyTorch Models on Azure Notebooks.mp4 16.8 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/10. Demo - Exploring and Preprocessing Data.mp4 16.4 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/11. Instantiating an Azure Deep Learning VM.mp4 16.3 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/07. Demo - Setting up a Deep Learning VM to Work with GPUs.mp4 16.2 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/10. Demo - Training a Linear Model Using Autograd.mp4 16.1 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/2. Persisting and Loading PyTorch Models/07. Saving Model Using the state_dict.mp4 16.0 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/09. Adding GPU Support to the VM and Installing the CUDA Toolkit.mp4 15.8 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/8. Style Transfer Using AlexNet.mp4 15.5 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/10. Using Convolution Filters to Detect Features.mp4 15.4 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/3. Implementing Training Using Single and Multiple Processors/3. Training Using Multiple Processes.mp4 15.0 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/4. Exploring and Transforming the Content and Style Images.mp4 15.0 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/4. Performing Multi-class Text Classification Using Characters/3. Loading and Cleaning Data.mp4 14.8 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/3. Exploring and Loading the Cats and Dogs Dataset.mp4 14.3 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/10. Distributed Data Loading in PyTorch.mp4 14.3 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/5. Training the Final Layer and Using the Model for Predict.mp4 14.2 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/16. Building Models with GPU Support on the AWS Deep Learning VM.mp4 13.8 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/02. Demo - Creating and Initializing Tensors.mp4 13.8 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/4. Performing Multi-class Text Classification Using Characters/6. Predicting Language from Names.mp4 13.6 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/12. Building PyTorch Models with GPU Support on Azure Deep Learning VMs.mp4 13.6 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/11. Demo - Defining the Neural Network and Helper Functions.mp4 13.4 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/07. Image Preprocessing - Resizing and Rescaling Images.mp4 13.4 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/05. Training the Target Image for Style Transfer.mp4 13.1 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/7. Training the Target Image to Perform Style Transfer.mp4 13.0 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/3. Implementing Training Using Single and Multiple Processors/5. Training on Multiple GPUs.mp4 13.0 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/05. Demo - Preparing Data.mp4 12.9 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/12. Demo - Setting up the Neural Network.mp4 12.9 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/8. Deploying a Model for Prediction to a Serverless Environment.mp4 12.8 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/5. Training a Simple Neural Network with One Neuron.mp4 12.8 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/06. Setting up a Deep Learning VM.mp4 12.6 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/7. Performing Image Classification with Pre-trained Models/3. Using the Resnet-18 Pretrained Model.mp4 12.6 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/11. Setting up a Deep Learning Virtual Machine on the Google Cloud Platfo.mp4 12.5 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/10. Building and Train a Neural Network for Bike Sharing Demand Prediction.mp4 12.5 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/2. Persisting and Loading PyTorch Models/05. Building and Training a Classifier Model.mp4 12.4 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/3. Understanding the Drawbacks of Using Deep Neural Networks with Images/3. Loading and Processing MNIST Images.mp4 12.4 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/08. Exploring the Bike Sharing Dataset.mp4 12.3 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/06. Demo - Building a Simple Neural Network to Perform Regression.mp4 12.3 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/11. Demo - Initializing the Ratings Matrix.mp4 12.1 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/02. Static vs. Dynamic Computation Graphs.mp4 12.1 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/09. Setting up a Deep Learning Virtual Machine.mp4 12.0 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/08. Designing a Multilayer Bidirectional RNN.mp4 11.9 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/10. Mean Average Precision @ K.mp4 11.8 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/07. Setting up a Convolutional Neural Network.mp4 11.8 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/08. Cropping and Denoising Images.mp4 11.8 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/5. Demo - Loading and Preparing Training Data.mp4 11.7 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/07. Designing an RNN for Binary Text Classification.mp4 11.6 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/4. Introducing Convolutional Neural Networks/4. Convolutional Layers.mp4 11.6 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/07. Demo - Building Static Computation Graphs with Tensorflow.mp4 11.6 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/09. Distributed Run Using the PyTorch Estimator.mp4 11.6 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/08. Training the RNN.mp4 11.5 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/4. Creating a Flask App to Serve the PyTorch Model.mp4 11.4 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/03. Demo - Simple Operations on Tensors.mp4 11.3 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/3. Understanding the Drawbacks of Using Deep Neural Networks with Images/2. Deep Neural Networks to Work with Images.mp4 11.3 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/07. Preparing Sentence Pairs.mp4 11.2 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/4. Creating PyTorch Solutions on the Google Cloud Platform/5. Create a Deep Learning VM with PyTorch and CUDA Support.mp4 11.2 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/07. Building a Custom Neural Network.mp4 11.2 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/09. Customizing and Evaluating Different Models.mp4 11.0 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/09. Hyperparameter Tuning.mp4 11.0 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/3. Implementing Training Using Single and Multiple Processors/4. Setting up a Deep Learning VM with Multiple GPUs.mp4 11.0 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/04. Building a Neural Network Using PyTorch Layers.mp4 11.0 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/08. Installing PyTorch with CPU Support Using Pip.mp4 10.9 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/2. Getting Started with PyTorch for Machine Learning/04. Representation Learning Using Neural Networks.mp4 10.8 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/12. Normalizing Images Using Mean and Standard Deviation.mp4 10.8 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/13. Model Deployment and Prediction Using Estimators.mp4 10.8 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/08. Demo - Preparing and Processing Data.mp4 10.7 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/4. Reusing Model Architectures and Designs/2. Exploring and Loading the Chest X-Ray Dataset.mp4 10.7 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/08. Training a CNN.mp4 10.7 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/2. Persisting and Loading PyTorch Models/04. Saving and Loading PyTorch Models.mp4 10.7 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/08. Designing the Encoder and Decoder.mp4 10.7 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/4. Reusing Model Architectures and Designs/3. Training a Model from Scratch.mp4 10.7 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/2. Uploading Datasets to Use for Image Classification.mp4 10.6 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/07. Demo - Introducing Autograd.mp4 10.6 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/2. Persisting and Loading PyTorch Models/08. Saving and Loading Checkpoints.mp4 10.6 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/04. CUDA Support in PyTorch.mp4 10.6 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/2. Implementing Recurrent Neural Networks (RNNs) in PyTorch/8. Long Memory Cells.mp4 10.5 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/6. Demo - Setting up Helper Functions.mp4 10.3 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/05. Exploring the Graduate Admissions Dataset.mp4 10.3 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/8. Performing Ridge Regression Using a Neural Network with One Neuron.mp4 10.2 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/10. Installing PyTorch with GPU Support Using Conda.mp4 10.2 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/06. Categorizing Transfer Learning.mp4 10.2 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/10. Pre-trained Models in PyTorch.mp4 10.1 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/6. Exploring and Loading the Oil Spill Dataset.mp4 10.1 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/2. Implementing Recurrent Neural Networks (RNNs) in PyTorch/7. Coping with Vanishing and Exploding Gradients.mp4 10.1 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/3. Understanding the Drawbacks of Using Deep Neural Networks with Images/5. Training a Fully Connected Image Classification Model.mp4 10.0 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/07. Demo - Exploring the Diamonds Dataset.mp4 10.0 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/2. Getting Started with PyTorch for Machine Learning/09. Demo - PyTorch Install and Setup.mp4 10.0 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/3. Implementing Training Using Single and Multiple Processors/2. Distributed Training Options in PyTorch.mp4 9.9 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/06. PyTorch Support for CUDA Devices.mp4 9.9 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/4. Setting up Training and Test Data Loaders.mp4 9.9 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/02. Understanding Generative Adversarial Networks (GANs).mp4 9.9 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/06. Setting up a Virtual Machine.mp4 9.9 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/5. Define the Training Function.mp4 9.9 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/07. Training the Discriminator.mp4 9.9 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/07. Matrix Factorization.mp4 9.7 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/10. Translating Sentences.mp4 9.7 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/2. Getting Started with PyTorch for Machine Learning/05. Neuron as a Mathematical Function.mp4 9.7 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/09. Demo - Working with the Device Context Manager.mp4 9.7 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/11. Working with Different Neural Network Architectures.mp4 9.5 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/05. Loading and Exploring the MNIST Handwritten Digit Images.mp4 9.4 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/4. Reusing Model Architectures and Designs/5. Fine-tuning the Network.mp4 9.4 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/09. Standardizing Images in PyTorch.mp4 9.3 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/3. Setting up a SageMaker Notebook Instance.mp4 9.3 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/04. Understanding the Leaky ReLU Activation Function.mp4 9.2 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/8. Additional Convolution Layers and Different Kernel Size.mp4 8.9 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/05. Preprocessing Images to Train Robust Models.mp4 8.9 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/4. Training the CNN.mp4 8.9 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/7. Performing Image Classification with Pre-trained Models/4. The Train Function to Find the Best Model Weights.mp4 8.9 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/05. Demo - Converting between PyTorch Tensors and NumPy Arrays.mp4 8.8 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/06. Setting up the Generator and Discriminator Neural Networks.mp4 8.7 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/7. Choosing Convolution Kernel Sizes.mp4 8.6 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/06. Preprocessing the Data.mp4 8.6 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/3. RNN Training and Long Memory Cells.mp4 8.6 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/04. Demo - Install and Setup Pytorch.mp4 8.6 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/05. Setup and Data Cleaning.mp4 8.5 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/7. Freezing Lower Layers and Fine-tuning Weights of Top Lay.mp4 8.5 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/03. Structural and Predictive Models.mp4 8.4 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/08. Training and Evaluating the Neural Network.mp4 8.4 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/08. Training the Generator and Generating Fake Images.mp4 8.4 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/5. Extracting Feature Maps from the Content and Style Images.mp4 8.4 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/07. Transfer Learning Scenarios.mp4 8.3 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/06. Preparing and Exploring Image Data.mp4 8.2 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/09. Performing Sentiment Analysis Using an RNN.mp4 8.2 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/3. Installing Libraries and Uploading Model Parameters to a GCP Bucket.mp4 8.1 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/2. Preparing the CIFAR-10 Dataset.mp4 8.1 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/7. Performing Image Classification with Pre-trained Models/2. Transfer Learning.mp4 8.1 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/5. Choosing Different Activation Functions.mp4 8.1 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/04. Demo - Elementwise and Matrix Operations on Tensors.mp4 8.1 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/4. Reusing Model Architectures and Designs/4. Exploring and Loading the Natural Images Dataset.mp4 8.0 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/08. Demo - Working with Gradients.mp4 8.0 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/2. Implementing Recurrent Neural Networks (RNNs) in PyTorch/6. Back Propagation through Time.mp4 7.8 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/08. Freeze or Fine-tune Layers.mp4 7.8 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/4. Using the VGG16 Model as a Fixed Feature Extractor.mp4 7.8 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/2. Getting Started with PyTorch for Machine Learning/06. Activation Functions.mp4 7.7 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/7. Preventing Overfitting Using Regularization.mp4 7.7 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/04. Calculating Gradients.mp4 7.7 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/4. Gradient Descent.mp4 7.6 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/02. Word Embeddings to Represent Text Data.mp4 7.6 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/04. Content, Style, and Target Images.mp4 7.6 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/6. Choosing Pooling Layers.mp4 7.6 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/04. Introducing Transfer Learning.mp4 7.6 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/03. Batch Normalization.mp4 7.5 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/04. Content Based Approaches to Recommendations.mp4 7.5 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/06. Setting up Helper Functions for Language Translation.mp4 7.5 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/8. Fine-tuning Top Layers.mp4 7.5 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/3. Loading the VGG19 Pretrained Model.mp4 7.5 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/6. Functions to Test and Save the Trained Model.mp4 7.4 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/08. Demo - Creating Tensors on CUDA-enabled Devices.mp4 7.3 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/3. Setting up the CNN.mp4 7.3 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/2. Implementing Recurrent Neural Networks (RNNs) in PyTorch/5. Recurrent Neurons.mp4 7.1 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/2. Getting Started with PyTorch for Machine Learning/08. TensorFlow and PyTorch.mp4 7.1 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/06. Bidirectional RNNs.mp4 7.0 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/02. Softmax and Cross Entropy.mp4 7.0 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/14. Demo - The Evaluate Helper Function.mp4 6.8 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/02. Zero Padding and Stride Size.mp4 6.8 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/04. Single Channel and Multichannel Images.mp4 6.8 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/03. Word Embeddings Capture Context and Meaning.mp4 6.8 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/4. Introducing Convolutional Neural Networks/5. Pooling Layers.mp4 6.7 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/02. Gradient Descent Optimization.mp4 6.6 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/4. Performing Multi-class Text Classification Using Characters/4. Helper Functions to One Hot Encode Names.mp4 6.6 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/2. Linear Regression.mp4 6.6 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/06. Content Loss.mp4 6.5 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/exercise.7z 6.5 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/2. Exploring Options to Deploy PyTorch Models.mp4 6.5 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/06. Two Passes in Reverse Mode Automatic Differentiation.mp4 6.3 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/09. Demo - Dynamic Computation Graphs in Tensorflow with Eager Execution.mp4 6.3 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/4. Introducing Convolutional Neural Networks/3. Understanding Convolution.mp4 6.3 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/05. Using Gradients to Update Model Parameters.mp4 6.2 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/4. Introducing Convolutional Neural Networks/6. Typical CNN Architecture.mp4 6.2 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/6. Calculating the Gram Matrix to Extract Style Information.mp4 6.2 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/08. Alternating Least Squares to Estimate the Ratings Matrix.mp4 6.1 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/03. Optimizers.mp4 6.0 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/08. Style Loss - Gram Matrix.mp4 6.0 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/2. Getting Started with PyTorch for Machine Learning/07. Introducing PyTorch.mp4 6.0 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/11. Image Transformations Using PyTorch Libraries.mp4 6.0 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/6. Visualizing Regression Results and Compare with Regression Using scikit-learn.mp4 6.0 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/06. Dropout.mp4 5.9 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/05. Collaborative Filtering.mp4 5.9 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/09. Using LSTM Cells and Dropout.mp4 5.9 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/2. Implementing Recurrent Neural Networks (RNNs) in PyTorch/4. RNNs for Natural Language Processing.mp4 5.8 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/6. Installing Docker.mp4 5.8 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/10. ZCA Whitening to Decorrelate Features.mp4 5.8 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/2. Distributed Training on the Cloud.mp4 5.7 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/02. Using Sequences and Vectors with RNNs.mp4 5.7 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/4. Creating PyTorch Solutions on the Google Cloud Platform/4. Prototyping PyTorch Models Using Cloud Datalab.mp4 5.7 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/09. Using Datasets and Data Loaders in PyTorch.mp4 5.6 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/11. Installing PyTorch with CUDA Support Using Pip.mp4 5.6 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/07. Style Loss - Cosine Similarity and Dot Products.mp4 5.6 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/06. Demo - Visualizing Neural Networks in PyTorch Using Hidden Layer.mp4 5.6 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/15. Demo - Building and Training the Recommendation System Neural Network.mp4 5.6 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/3. Finding the Best Fit Line.mp4 5.5 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/2. The Recurrent Neuron.mp4 5.4 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/04. Feeding Text Data into RNNs.mp4 5.4 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/3. Understanding the Drawbacks of Using Deep Neural Networks with Images/4. Setting up a Fully Connected Neural Network for Image Classification.mp4 5.3 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/03. Training a GAN.mp4 5.2 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/05. Teacher Forcing.mp4 5.2 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/4. RNN to Generate Names in Languages.mp4 5.2 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/03. Forward and Backward Passes.mp4 5.2 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/05. Source and Target Domains, Source and Target Tasks.mp4 5.1 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/03. Clustering.mp4 5.1 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/05. Training a Neural Network Using Optimizers.mp4 5.0 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/05. PyTorch - Taxonomy of Solutions.mp4 5.0 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/7. Performing Image Classification with Pre-trained Models/5. Predictions Using Pretrained Models.mp4 4.9 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/4. Creating PyTorch Solutions on the Google Cloud Platform/6. Using JupyterLab on a GCP Deep Learning VM.mp4 4.9 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/01. Finding Patterns in Data.mp4 4.7 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/5. Using the Model for Prediction.mp4 4.7 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/04. Azure Machine Learning Service Workflow.mp4 4.7 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/03. Softmax and LogSoftmax.mp4 4.7 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/02. Numeric Representations of Words.mp4 4.6 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/05. Exploring PyTorch Install Options on a Local Machine.mp4 4.6 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/1. Text as Sequential Data.mp4 4.5 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/4. Introducing Convolutional Neural Networks/2. Local Receptive Fields.mp4 4.5 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/02. Training a Neural Network Forward and Backward Passes.mp4 4.4 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/05. Demo - Building Dynamic Computations Graphs with PyTorch.mp4 4.3 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.mp4 4.3 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/4. Creating PyTorch Solutions on the Google Cloud Platform/2. Cloud Datalab and Deep Learning VMs.mp4 4.3 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/09. Evaluation Metrics vs. Loss Metrics.mp4 4.3 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/06. Nearest Neighborhood.mp4 4.2 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/08. Demo - Visualizing Tensorflow Graphs with Tensorboard.mp4 4.1 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.mp4 4.0 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/04. Machine Learning on the Cloud.mp4 4.0 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/06. Introducing SageMaker.mp4 4.0 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/2. Pretrained Models for Style Transfer.mp4 4.0 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.mp4 4.0 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/05. Understanding Terms in Azure Machine Learning.mp4 4.0 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.mp4 4.0 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/04. Activation Functions.mp4 3.9 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.mp4 3.9 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/exercise.7z 3.8 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/09. Benefits of Transfer Learning.mp4 3.8 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/09. Demo - Variables and Tensors.mp4 3.8 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/03. Introducing torchtext to Process Text Data.mp4 3.8 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/02. Association Rule Learning.mp4 3.8 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.mp4 3.6 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.mp4 3.6 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.mp4 3.5 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/04. Evaluating Classifiers.mp4 3.4 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/4. Performing Multi-class Text Classification Using Characters/2. Language Prediction Based on Names.mp4 3.4 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/01. Module Overview.mp4 3.4 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/05. Feature Map Size Calculations.mp4 3.3 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/11. Summary and Further Study.mp4 3.3 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/04. Demo - Installing Tensorflow, Graphviz, and Hidden Layer.mp4 3.2 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.mp4 3.1 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/2. Persisting and Loading PyTorch Models/02. Module Overview.mp4 3.0 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/03. Language Translation Using Encoders and Decoders.mp4 3.0 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/2. Getting Started with PyTorch for Machine Learning/03. Prerequisites and Course Outline.mp4 2.9 MB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/2. Persisting and Loading PyTorch Models/09. Introducing ONNX.mp4 2.9 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/05. Multilayer RNNs.mp4 2.8 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/04. Representing Input and Target Sentences.mp4 2.8 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/02. Prerequisites and Course Outline.mp4 2.8 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/09. Cleaning up Resources.mp4 2.8 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/1. Module Overview.mp4 2.8 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/02. Introducing Azure Machine Learning Service.mp4 2.8 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/14. AWS Deep Learning AMIs.mp4 2.7 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/10. Summary and Further Study.mp4 2.7 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/07. Epochs and Batches.mp4 2.7 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/4. Reusing Model Architectures and Designs/6. Cleaning up Resources.mp4 2.7 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/10. The Azure Deep Learning VM.mp4 2.6 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/01. Module Overview.mp4 2.5 MB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/09. PyTorch Estimators on SageMaker.mp4 2.5 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/4. Reusing Model Architectures and Designs/1. Module Overview.mp4 2.5 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/10. Summary and Further Study.mp4 2.4 MB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/03. Prerequisites and Course Outline.mp4 2.4 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/03. Prerequisites and Course Outline.mp4 2.4 MB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/9. Module Summary.mp4 2.4 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/11. Summary and Further Study.mp4 2.4 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/2. Implementing Recurrent Neural Networks (RNNs) in PyTorch/3. Prerequisites and Course Outline.mp4 2.4 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/7. Performing Image Classification with Pre-trained Models/6. Cleaning up Resources.mp4 2.4 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/3. Understanding the Drawbacks of Using Deep Neural Networks with Images/1. Module Overview.mp4 2.4 MB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/2. Implementing Recurrent Neural Networks (RNNs) in PyTorch/9. Module Summary.mp4 2.3 MB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/02. Module Overview.mp4 2.3 MB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/10. Debugging in PyTorch and Tensorflow.mp4 2.2 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/7. Performing Image Classification with Pre-trained Models/7. Summary and Further Study.mp4 2.2 MB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/16. Summary and Further Study.mp4 2.2 MB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/10. Module Summary.mp4 2.2 MB
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  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/08. Exploring the Bike Sharing Dataset.vtt 7.7 kB
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  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/04. Building a Neural Network Using PyTorch Layers.vtt 7.6 kB
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  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/04. Calculating Gradients.vtt 7.6 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/2. Persisting and Loading PyTorch Models/05. Building and Training a Classifier Model.vtt 7.6 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/2. Getting Started with PyTorch for Machine Learning/06. Activation Functions.vtt 7.6 kB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/4. Creating PyTorch Solutions on the Google Cloud Platform/5. Create a Deep Learning VM with PyTorch and CUDA Support.vtt 7.6 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/6. Exploring and Loading the Oil Spill Dataset.vtt 7.5 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/3. Understanding the Drawbacks of Using Deep Neural Networks with Images/5. Training a Fully Connected Image Classification Model.vtt 7.5 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/05. Demo - Converting between PyTorch Tensors and NumPy Arrays.vtt 7.5 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/11. Demo - Defining the Neural Network and Helper Functions.vtt 7.5 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/03. Batch Normalization.vtt 7.5 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/08. Training the RNN.vtt 7.5 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/03. Structural and Predictive Models.vtt 7.4 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/08. Demo - Working with Gradients.vtt 7.4 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/04. Demo - Elementwise and Matrix Operations on Tensors.vtt 7.4 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/8. Performing Ridge Regression Using a Neural Network with One Neuron.vtt 7.4 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/09. Demo - Working with the Device Context Manager.vtt 7.3 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/02. Word Embeddings to Represent Text Data.vtt 7.3 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/2. Exploring Options to Deploy PyTorch Models.vtt 7.2 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/08. Freeze or Fine-tune Layers.vtt 7.2 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/12. Demo - Setting up the Neural Network.vtt 7.2 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/06. Setting up a Deep Learning VM.vtt 7.2 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/09. Adding GPU Support to the VM and Installing the CUDA Toolkit.vtt 7.2 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/09. Standardizing Images in PyTorch.vtt 7.2 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/04. Introducing Transfer Learning.vtt 7.1 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/2. Implementing Recurrent Neural Networks (RNNs) in PyTorch/6. Back Propagation through Time.vtt 7.1 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/07. Preparing Sentence Pairs.vtt 7.1 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/05. Exploring the Graduate Admissions Dataset.vtt 7.1 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/08. Cropping and Denoising Images.vtt 7.0 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/07. Designing an RNN for Binary Text Classification.vtt 7.0 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/3. RNN Training and Long Memory Cells.vtt 6.9 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/07. Training the Discriminator.vtt 6.9 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/09. Customizing and Evaluating Different Models.vtt 6.9 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/4. Gradient Descent.vtt 6.9 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/2. Getting Started with PyTorch for Machine Learning/08. TensorFlow and PyTorch.vtt 6.9 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/08. Training a CNN.vtt 6.9 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/09. Setting up a Deep Learning Virtual Machine.vtt 6.9 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/2. Implementing Recurrent Neural Networks (RNNs) in PyTorch/5. Recurrent Neurons.vtt 6.8 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/04. Single Channel and Multichannel Images.vtt 6.8 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/4. Training the CNN.vtt 6.8 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/7. Performing Image Classification with Pre-trained Models/4. The Train Function to Find the Best Model Weights.vtt 6.7 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/4. Setting up Training and Test Data Loaders.vtt 6.7 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/6. Demo - Setting up Helper Functions.vtt 6.7 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/2. Getting Started with PyTorch for Machine Learning/07. Introducing PyTorch.vtt 6.7 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/5. Define the Training Function.vtt 6.7 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/2. Linear Regression.vtt 6.6 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/08. Designing the Encoder and Decoder.vtt 6.6 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/02. Gradient Descent Optimization.vtt 6.6 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/4. Reusing Model Architectures and Designs/2. Exploring and Loading the Chest X-Ray Dataset.vtt 6.6 kB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/13. Model Deployment and Prediction Using Estimators.vtt 6.5 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/06. Two Passes in Reverse Mode Automatic Differentiation.vtt 6.5 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/02. Softmax and Cross Entropy.vtt 6.5 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/09. Hyperparameter Tuning.vtt 6.5 kB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/09. Distributed Run Using the PyTorch Estimator.vtt 6.5 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/06. Bidirectional RNNs.vtt 6.4 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/11. Setting up a Deep Learning Virtual Machine on the Google Cloud Platfo.vtt 6.4 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/3. Working PyTorch Tensors/08. Demo - Creating Tensors on CUDA-enabled Devices.vtt 6.4 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/08. Demo - Preparing and Processing Data.vtt 6.4 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/07. Demo - Exploring the Diamonds Dataset.vtt 6.4 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/05. Loading and Exploring the MNIST Handwritten Digit Images.vtt 6.3 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/4. Reusing Model Architectures and Designs/4. Exploring and Loading the Natural Images Dataset.vtt 6.2 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/03. Optimizers.vtt 6.2 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/06. Content Loss.vtt 6.2 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/2. Persisting and Loading PyTorch Models/08. Saving and Loading Checkpoints.vtt 6.2 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/06. Preparing and Exploring Image Data.vtt 6.2 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/2. Distributed Training on the Cloud.vtt 6.2 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/4. Creating a Flask App to Serve the PyTorch Model.vtt 6.1 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/06. Demo - Building a Simple Neural Network to Perform Regression.vtt 6.1 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/06. Setting up a Virtual Machine.vtt 6.1 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/03. Word Embeddings Capture Context and Meaning.vtt 6.0 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/5. Building Convolutional Neural Networks for Image Classification/02. Zero Padding and Stride Size.vtt 6.0 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/2. Implementing Recurrent Neural Networks (RNNs) in PyTorch/4. RNNs for Natural Language Processing.vtt 6.0 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/04. Content, Style, and Target Images.vtt 5.9 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/04. Content Based Approaches to Recommendations.vtt 5.9 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/05. Using Gradients to Update Model Parameters.vtt 5.9 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/10. Translating Sentences.vtt 5.8 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/02. Using Sequences and Vectors with RNNs.vtt 5.8 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/3. Implementing Training Using Single and Multiple Processors/4. Setting up a Deep Learning VM with Multiple GPUs.vtt 5.7 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/4. Introducing Convolutional Neural Networks/3. Understanding Convolution.vtt 5.7 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/08. Training and Evaluating the Neural Network.vtt 5.7 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/08. Style Loss - Gram Matrix.vtt 5.7 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/4. Reusing Model Architectures and Designs/5. Fine-tuning the Network.vtt 5.7 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/2. Understanding Neural Style Transfer/07. Style Loss - Cosine Similarity and Dot Products.vtt 5.7 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/8. Additional Convolution Layers and Different Kernel Size.vtt 5.7 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/4. Using the VGG16 Model as a Fixed Feature Extractor.vtt 5.6 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/05. Setup and Data Cleaning.vtt 5.6 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/06. Demo - Visualizing Neural Networks in PyTorch Using Hidden Layer.vtt 5.6 kB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/05. PyTorch - Taxonomy of Solutions.vtt 5.6 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/3. Loading the VGG19 Pretrained Model.vtt 5.5 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/06. Setting up the Generator and Discriminator Neural Networks.vtt 5.4 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/2. Uploading Datasets to Use for Image Classification.vtt 5.4 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/09. Demo - Dynamic Computation Graphs in Tensorflow with Eager Execution.vtt 5.4 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/5. Extracting Feature Maps from the Content and Style Images.vtt 5.4 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/8. Fine-tuning Top Layers.vtt 5.3 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/2. Preparing the CIFAR-10 Dataset.vtt 5.3 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/06. Setting up Helper Functions for Language Translation.vtt 5.3 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/06. Preprocessing the Data.vtt 5.2 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/08. Alternating Least Squares to Estimate the Ratings Matrix.vtt 5.2 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/4. Introducing Convolutional Neural Networks/5. Pooling Layers.vtt 5.2 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/09. Performing Sentiment Analysis Using an RNN.vtt 5.2 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/playlist.m3u 5.2 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/3. Setting up a SageMaker Notebook Instance.vtt 5.2 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/4. Introducing Convolutional Neural Networks/6. Typical CNN Architecture.vtt 5.0 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/03. Training a GAN.vtt 5.0 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/3. Finding the Best Fit Line.vtt 5.0 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/3. Setting up the CNN.vtt 5.0 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/4. RNN to Generate Names in Languages.vtt 5.0 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/05. Teacher Forcing.vtt 4.9 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/2. Implementing Predictive Analytics with Numeric Data/04. Demo - Install and Setup Pytorch.vtt 4.9 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/2. Getting Started with Transfer Learning/05. Source and Target Domains, Source and Target Tasks.vtt 4.8 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/03. Forward and Backward Passes.vtt 4.8 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/04. Feeding Text Data into RNNs.vtt 4.7 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/11. Working with Different Neural Network Architectures.vtt 4.7 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/4. Implementing Distributed Training on Multiple Machines/6. Functions to Test and Save the Trained Model.vtt 4.7 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/08. Installing PyTorch with CPU Support Using Pip.vtt 4.7 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/2. Installing PyTorch on a Local Machine/10. Installing PyTorch with GPU Support Using Conda.vtt 4.7 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/playlist.m3u 4.6 kB
  • C1. Expediting Deep Learning with Transfer Learning. PyTorch Playbook (Janani Ravi, 2019)/3. Performing Feature Extraction Using Transfer Learning/7. Freezing Lower Layers and Fine-tuning Weights of Top Lay.vtt 4.6 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/01. Finding Patterns in Data.vtt 4.6 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/6. Calculating the Gram Matrix to Extract Style Information.vtt 4.6 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/11. Image Transformations Using PyTorch Libraries.vtt 4.5 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/05. Collaborative Filtering.vtt 4.5 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/2. The Recurrent Neuron.vtt 4.4 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/4. Performing Multi-class Text Classification Using Characters/4. Helper Functions to One Hot Encode Names.vtt 4.4 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/5. Performing Sentiment Analysis Using Word Embeddings/02. Numeric Representations of Words.vtt 4.4 kB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/4. Creating PyTorch Solutions on the Google Cloud Platform/2. Cloud Datalab and Deep Learning VMs.vtt 4.4 kB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/04. Machine Learning on the Cloud.vtt 4.4 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/4. Building Generative Adversarial Networks in PyTorch/08. Training the Generator and Generating Fake Images.vtt 4.3 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/3. Understanding the Drawbacks of Using Deep Neural Networks with Images/4. Setting up a Fully Connected Neural Network for Image Classification.vtt 4.3 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/2. Preprocessing Images to Use in Machine Learning Models/10. ZCA Whitening to Decorrelate Features.vtt 4.3 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/05. Demo - Building Dynamic Computations Graphs with PyTorch.vtt 4.2 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/06. Dropout.vtt 4.2 kB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/2. Creating PyTorch Solutions on AWS/06. Introducing SageMaker.vtt 4.2 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/5. Choosing Different Activation Functions.vtt 4.2 kB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/05. Understanding Terms in Azure Machine Learning.vtt 4.1 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/6. Installing Docker.vtt 4.1 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/3. Performing Binary Text Classification Using Words/03. Introducing torchtext to Process Text Data.vtt 4.1 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/3. Implementing Predictive Analytics with Text Data/1. Text as Sequential Data.vtt 4.1 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/6. Choosing Pooling Layers.vtt 4.0 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/3. Understanding Linear Regression with a Single Neuron/6. Visualizing Regression Results and Compare with Regression Using scikit-learn.vtt 4.0 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/7. Performing Image Classification with Pre-trained Models/5. Predictions Using Pretrained Models.vtt 4.0 kB
  • C3. Deploying PyTorch Models in Production. PyTorch Playbook (Janani Ravi, 2019)/5. Deploying PyTorch Models to Production/3. Installing Libraries and Uploading Model Parameters to a GCP Bucket.vtt 4.0 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/03. Softmax and LogSoftmax.vtt 4.0 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/5. Building Dynamic Computation Graphs/08. Demo - Visualizing Tensorflow Graphs with Tensorboard.vtt 3.9 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/playlist.m3u 3.9 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/02. Training a Neural Network Forward and Backward Passes.vtt 3.8 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/4. Building a Regression Model Using PyTorch/09. Using Datasets and Data Loaders in PyTorch.vtt 3.8 kB
  • A3. Using PyTorch in the Cloud. PyTorch Playbook (Janani Ravi, 2019)/3. Creating PyTorch Solutions on Azure/04. Azure Machine Learning Service Workflow.vtt 3.8 kB
  • B1. Image Classification with PyTorch (Janani Ravi, 2019)/6. Optimizing Image Classification with Hyperparameter Tuning/7. Choosing Convolution Kernel Sizes.vtt 3.7 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/playlist.m3u 3.7 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/playlist.m3u 3.7 kB
  • C2. Predictive Analytics with PyTorch (Janani Ravi, 2020)/4. Implementing Predictive Analytics with User Preference Data/09. Evaluation Metrics vs. Loss Metrics.vtt 3.6 kB
  • A1. Foundations of PyTorch (Janani Ravi, 2019)/4. Working with Gradients Using the Autograd Library/09. Demo - Variables and Tensors.vtt 3.6 kB
  • B3. Natural Language Processing with PyTorch (Janani Ravi, 2019)/6. Performing Language Translation Using Sequence-to-Sequence Models/11. Summary and Further Study.vtt 3.6 kB
  • B2. Style Transfer with PyTorch (Janani Ravi, 2019)/3. Implementing Neural Style Transfer in PyTorch/2. Pretrained Models for Style Transfer.vtt 3.5 kB
  • A2. Building Your First PyTorch Solution (Janani Ravi, 2019)/5. Building a Classification Model Using PyTorch/04. Evaluating Classifiers.vtt 3.5 kB
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