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- 01 Course Overview Installs and Setup/002 Course Setup and Installation.mp4 159.8 MB
- 13 Deployment/114 Flask Front End.mp4 156.9 MB
- 09 Recurrent Neural Networks - RNNs/088 Bonus - Multivariate Time Series - RNN and LSTMs.mp4 156.6 MB
- 09 Recurrent Neural Networks - RNNs/087 RNN Exercise - Solutions.mp4 155.3 MB
- 07 Basic Artificial Neural Networks - ANNs/057 Tensorboard.mp4 151.2 MB
- 07 Basic Artificial Neural Networks - ANNs/050 Keras Project Solutions - Exploratory Data Analysis.mp4 150.6 MB
- 07 Basic Artificial Neural Networks - ANNs/042 Keras Regression Code Along - Exploratory Data Analysis.mp4 143.7 MB
- 12 Generative Adversarial Networks/106 Creating a GAN - Part Three - Model Training.mp4 138.0 MB
- 09 Recurrent Neural Networks - RNNs/085 RNN on a Time Series - Part Two.mp4 137.4 MB
- 13 Deployment/115 Live Deployment to the Web.mp4 132.7 MB
- 07 Basic Artificial Neural Networks - ANNs/053 Keras Project Solutions - Categorical Data.mp4 131.1 MB
- 11 AutoEncoders/098 Autoencoder for Dimensionality Reduction.mp4 123.2 MB
- 07 Basic Artificial Neural Networks - ANNs/047 Keras Classification - Dealing with Overfitting and Evaluation.mp4 116.7 MB
- 01 Course Overview Installs and Setup/002 FINAL-TF2-FILES.zip 104.1 MB
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- 08 Convolutional Neural Networks - CNNs/064 CNN on MNIST - Part Two - Creating and Training the Model.mp4 103.7 MB
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- 05 Visualization Crash Course/022 Seaborn Basics.mp4 96.3 MB
- 02 Download Code and Setup Colab/1 Modern Computer Vision__2022-02-25.7z 120.8 MB
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- 18 Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/2 Loading Pre-Trained Networks in PyTorch (ResNets, DenseNets, MobileNET, VGG19).mkv 3.2 MB
- 09 OpenCV Projects/06 Neural Style Transfer with OpenCV.mkv 2.9 MB
- 26 Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/5 DeepFace - Age, Gender, Emotion, Ethnicity and Face Recognition.mkv 2.7 MB
- 18 Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/1 Implementing LeNet and AlexNet in Keras.mkv 2.7 MB
- 04 OpenCV - Image Segmentation/2 Moments, Sorting, Approximating and Matching Contours.mkv 2.7 MB
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- 21 Transfer Learning and Fine Tuning/4 Keras Feature Extraction.mkv 2.5 MB
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- 09 OpenCV Projects/03 OCR with PyTesseract and EasyOCR (Text Detection).mkv 2.4 MB
- 29 Gun Detector - Scaled-YOLOv4/1 Gun Detector - Scaled-YOLOv4.mkv 2.4 MB
- 18 Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/3 Loading Pre-Trained Networks in Keras (ResNets, DenseNets, MobileNET, VGG19).mkv 2.4 MB
- 19 Using Callbacks in Keras and PyTorch/2 Cats vs Dogs Classifier Using Callbacks in PyTorch.mkv 2.3 MB
- 24 Generative Adversarial Networks (GANs)/5 Keras DCGAN with MNIST.mkv 2.2 MB
- 03 OpenCV - Image Operations/01 Getting Started with OpenCV4.mkv 2.2 MB
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- ~Get Your Files Here !/04 - 3. Chapter Name/10 - Training ADNN using embeddings.mp4 15.4 MB
- ~Get Your Files Here !/04 - 3. Chapter Name/03 - Representing text using count vectorization.mp4 14.9 MB
- ~Get Your Files Here !/03 - 2. Chapter Name/04 - Cleaning and preprocessing text.mp4 13.5 MB
- ~Get Your Files Here !/04 - 3. Chapter Name/07 - Representing text using TFIDF vectorization.mp4 9.5 MB
- ~Get Your Files Here !/02 - 1. Chapter Name/02 - Word vector encodings and word embeddings.mp4 9.4 MB
- ~Get Your Files Here !/04 - 3. Chapter Name/04 - Configuring the dense neural network (DNN).mp4 9.4 MB
- ~Get Your Files Here !/02 - 1. Chapter Name/04 - Approaches and challenges in sentiment analysis.mp4 9.0 MB
- ~Get Your Files Here !/05 - 4. Chapter Name/02 - Long memory cells.mp4 8.9 MB
- ~Get Your Files Here !/05 - 4. Chapter Name/04 - Training a recurrent neural network.mp4 8.1 MB
- ~Get Your Files Here !/04 - 3. Chapter Name/08 - Training and evaluating the model.mp4 8.0 MB
- ~Get Your Files Here !/03 - 2. Chapter Name/02 - Importing Python modules and loading data.mp4 7.8 MB
- ~Get Your Files Here !/04 - 3. Chapter Name/01 - Feed-forward neural networks.mp4 7.7 MB
- ~Get Your Files Here !/03 - 2. Chapter Name/03 - Analyzing word lengths across sentiment categories.mp4 7.6 MB
- ~Get Your Files Here !/01 - Introduction/01 - An overview of sentiment analysis.mp4 7.6 MB
- ~Get Your Files Here !/05 - 4. Chapter Name/05 - Training an LSTM network.mp4 7.3 MB
- ~Get Your Files Here !/04 - 3. Chapter Name/02 - Splitting data into training test and validation sets.mp4 7.3 MB
- ~Get Your Files Here !/04 - 3. Chapter Name/05 - Training and evaluating the DNN.mp4 6.9 MB
- ~Get Your Files Here !/05 - 4. Chapter Name/06 - Serializing a model to disk and loading the model.mp4 6.8 MB
- ~Get Your Files Here !/03 - 2. Chapter Name/01 - Getting set up with Google Colab.mp4 6.7 MB
- ~Get Your Files Here !/05 - 4. Chapter Name/01 - Recurrent neural networks.mp4 6.5 MB
- ilearn-annawkipar.r00 50.0 MB
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- 01 - Introduction/001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit.mp4 153.4 MB
- 02 - TensorFlow 2.0 Basics/001 From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
- 17 - Annex 3 - Recurrent Neural Networks Theory/005 LSTM Practical Intuition.mp4 112.7 MB
- 17 - Annex 3 - Recurrent Neural Networks Theory/004 LSTMs.mp4 93.2 MB
- 16 - Annex 2 - Convolutional Neural Networks Theory/005 Step 2 - Max Pooling.mp4 91.7 MB
- 17 - Annex 3 - Recurrent Neural Networks Theory/003 Vanishing Gradient.mp4 90.4 MB
- 16 - Annex 2 - Convolutional Neural Networks Theory/002 What are Convolutional Neural Networks.mp4 74.5 MB
- 16 - Annex 2 - Convolutional Neural Networks Theory/003 Step 1 - Convolution.mp4 68.8 MB
- 10 - Dataset Preprocessing with TensorFlow Transform (TFT)/005 Dataset preprocessing pipeline.mp4 62.7 MB
- 16 - Annex 2 - Convolutional Neural Networks Theory/007 Step 4 - Full Connection.mp4 61.4 MB
- 17 - Annex 3 - Recurrent Neural Networks Theory/002 What are Recurrent Neural Networks.mp4 60.3 MB
- 04 - Convolutional Neural Networks/002 Building the Convolutional Neural Network.mp4 59.3 MB
- 07 - Deep Reinforcement Learning Theory/009 Action Selection Policies.mp4 57.0 MB
- 16 - Annex 2 - Convolutional Neural Networks Theory/009 Softmax & Cross-Entropy.mp4 53.9 MB
- 07 - Deep Reinforcement Learning Theory/002 The Bellman Equation.mp4 50.6 MB
- 06 - Transfer Learning and Fine Tuning/001 What is Transfer Learning.mp4 48.7 MB
- 06 - Transfer Learning and Fine Tuning/002 Project Setup.mp4 46.6 MB
- 15 - Annex 1 - Artificial Neural Networks Theory/002 The Neuron.mp4 45.8 MB
- 15 - Annex 1 - Artificial Neural Networks Theory/005 How do Neural Networks Learn.mp4 45.4 MB
- 07 - Deep Reinforcement Learning Theory/003 Markov Decision Process (MDP).mp4 44.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
- 1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
- 7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/4. LSTMs.mp4 143.1 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/2. What are Recurrent Neural Networks.mp4 126.8 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/9. Softmax & Cross-Entropy.mp4 123.6 MB
- 2. TensorFlow 2.0 Basics/1. From TensorFlow 1.x to TensorFlow 2.0.mp4 120.4 MB
- 7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
- 15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/3. Vanishing Gradient.mp4 116.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/2. What are Convolutional Neural Networks.mp4 113.1 MB
- 7. Deep Reinforcement Learning Theory/6. Deep Q-Learning Intuition - Step 1.mp4 104.8 MB
- 15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
- 7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
- 7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
- 7. Deep Reinforcement Learning Theory/3. Markov Decision Process (MDP).mp4 98.9 MB
- 4. Convolutional Neural Networks/2. Building the Convolutional Neural Network.mp4 92.5 MB
- 11. Python - Solving a Regression problem using ANN/1. Building Neural Network for Regression Problem.mp4 163.5 MB
- 13. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 158.9 MB
- 4. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 128.1 MB
- 15. Add-on 1 Data Preprocessing/13. Bi-variate analysis and Variable transformation.mp4 105.3 MB
- 16. Add-on 2 Classic ML models - Linear Regression/3. Assessing accuracy of predicted coefficients.mp4 96.6 MB
- 12. Complex ANN Architectures using Functional API/1. Using Functional API for complex architectures.mp4 96.6 MB
- 3. Single Cells - Perceptron and Sigmoid Neuron/3. Python - Creating Perceptron model.mp4 90.8 MB
- 10. Python - Building and training the Model/3. Compiling and Training the Neural Network model.mp4 85.7 MB
- 10. Python - Building and training the Model/2. Building the Neural Network using Keras.mp4 83.0 MB
- 15. Add-on 1 Data Preprocessing/18. Correlation Analysis.mp4 75.1 MB
- 15. Add-on 1 Data Preprocessing/9. Outlier Treatment in Python.mp4 73.6 MB
- 10. Python - Building and training the Model/4. Evaluating performance and Predicting using Keras.mp4 73.3 MB
- 16. Add-on 2 Classic ML models - Linear Regression/9. Multiple Linear Regression in Python.mp4 73.1 MB
- 15. Add-on 1 Data Preprocessing/3. The Dataset and the Data Dictionary.mp4 72.7 MB
- 2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp4 68.3 MB
- 2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4 67.6 MB
- 16. Add-on 2 Classic ML models - Linear Regression/5. Simple Linear Regression in Python.mp4 66.5 MB
- 5. Important concepts Common Interview questions/1. Some Important Concepts.mp4 65.2 MB
- 15. Add-on 1 Data Preprocessing/7. EDD in Python.mp4 64.8 MB
- 14. Hyperparameter Tuning/1. Hyperparameter Tuning.mp4 63.6 MB
- ZERO TO DEEP LEARNING WITH PYTHON AND KERAS/[FreeTutorials.Us] zero-to-deep-learning/[FreeTutorials.Us].txt 75 Bytes
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- 16. Annex 2 - Convolutional Neural Networks Theory/7. Step 4 - Full Connection.mp4 203.6 MB
- 17. Annex 3 - Recurrent Neural Networks Theory/5. LSTM Practical Intuition.mp4 196.5 MB
- 1. Introduction/1. Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit..mp4 153.4 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.srt 147.0 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/5. Step 2 - Max Pooling.mp4 147.0 MB
- 7. Deep Reinforcement Learning Theory/9. Action Selection Policies.mp4 143.5 MB
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- 7. Deep Reinforcement Learning Theory/8. Experience Replay.mp4 120.3 MB
- 15. Annex 1 - Artificial Neural Networks Theory/5. How do Neural Networks Learn.mp4 117.6 MB
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- 15. Annex 1 - Artificial Neural Networks Theory/2. The Neuron.mp4 103.5 MB
- 16. Annex 2 - Convolutional Neural Networks Theory/3. Step 1 - Convolution.mp4 102.6 MB
- 7. Deep Reinforcement Learning Theory/5. Temporal Difference.mp4 101.8 MB
- 7. Deep Reinforcement Learning Theory/2. The Bellman Equation.mp4 99.7 MB
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