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[LinkedIn Learning] Getting Started with AI and Machine Learning - Complete 7 Courses
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[LinkedIn Learning] Getting Started with AI and Machine Learning - Complete 7 Courses
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文件列表
Building Computer Vision Applications with Python/Ex_Files_Computer_Vision_Deep_Dive_in_Python.zip
152.8 MB
Building Computer Vision Applications with Python/6 - Fun with Cuts/2. Stitching two images together.mp4
46.3 MB
Machine Learning Foundations Linear Algebra/2 - Vectors Basics/1. Introduction to vectors.mp4
31.4 MB
Building Computer Vision Applications with Python/4 - Filters/3. Median filters.mp4
26.6 MB
Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/2. Applications of linear algebra in ML.mp4
23.9 MB
Building Computer Vision Applications with Python/3 - From Color to Black and White/4. Adaptive thresholding.mp4
22.0 MB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/3. Image file management.mp4
20.1 MB
Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/3. Markov decision process.mp4
18.2 MB
Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/3. Changing basis of vectors.mp4
18.0 MB
Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/1. Solving linear equations using Gaussian elimination.mp4
17.9 MB
Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/1. Match patterns.mp4
16.3 MB
Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/1. Convolutional neural networks (CNN).mp4
16.3 MB
Reinforcement Learning Foundations/4 - Temporal Difference Methods/2. SARSA.mp4
15.9 MB
Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/2. A basic RL problem.mp4
15.8 MB
Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/2. Natural language processing.mp4
15.2 MB
Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/2. Transforming to the new basis.mp4
15.1 MB
Hands-On PyTorch Machine Learning/5 - Torchtext/2. Torchtext for translation.mp4
15.0 MB
Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/1. Robotics.mp4
14.9 MB
Building Computer Vision Applications with Python/4 - Filters/5. Edge detection filters.mp4
14.9 MB
Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/3. Perceptrons.mp4
14.8 MB
Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/4. Plan AI.mp4
14.6 MB
Building Computer Vision Applications with Python/7 - Morphological Modifications/1. Why modify objects.mp4
14.5 MB
Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/1. Machine learning.mp4
14.4 MB
Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/2. Scalar and vector projection.mp4
14.4 MB
Building Computer Vision Applications with Python/6 - Fun with Cuts/1. Image cuts.mp4
14.4 MB
Hands-On PyTorch Machine Learning/3 - Torchvision/1. Torchvision introduction.mp4
14.4 MB
Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/3. Unsupervised learning.mp4
14.3 MB
Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/5. Regression.mp4
14.2 MB
Hands-On PyTorch Machine Learning/4 - Torchaudio/2. Torchaudio for audio understanding.mp4
13.9 MB
Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/3. Changing to the eigenbasis.mp4
13.8 MB
Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/2. Artificial neural networks.mp4
13.7 MB
Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/2. Data science.mp4
13.7 MB
Hands-On PyTorch Machine Learning/1 - Preparation/2. PyTorch environment setup.mp4
13.7 MB
Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/3. Strong vs. weak AI.mp4
13.6 MB
Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/4. Backpropagation.mp4
13.6 MB
Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/2. Recurrent neural networks (RNN).mp4
13.4 MB
Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/1. Big data.mp4
13.3 MB
Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/2. Foundation models.mp4
13.2 MB
Building Computer Vision Applications with Python/6 - Fun with Cuts/3. Cuts in panoramic photography.mp4
13.1 MB
Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/4. Google PageRank algorithm.mp4
13.0 MB
Machine Learning Foundations Linear Algebra/2 - Vectors Basics/2. Vector arithmetic.mp4
13.0 MB
Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/1. Dot product of vectors.mp4
13.0 MB
Artificial Intelligence Foundations Thinking Machines/7 - Avoiding Pitfalls/1. Pitfalls.mp4
12.9 MB
Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/1. Monte Carlo method.mp4
12.8 MB
Hands-On PyTorch Machine Learning/1 - Preparation/4. PyTorch data exploration.mp4
12.7 MB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/1. Image representation.mp4
12.7 MB
Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/4. Basis, linear independence, and span.mp4
12.6 MB
Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/1. Define general intelligence.mp4
12.5 MB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/4. Regularization techniques to improve overfitting models.mp4
12.4 MB
Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/4. Composition or combination of matrix transformations.mp4
12.3 MB
Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/3. The Internet of Things.mp4
12.3 MB
Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/1. Generative AI.mp4
12.2 MB
Building Computer Vision Applications with Python/5 - Image Scaling/4. Upscaling example.mp4
12.2 MB
Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/2. Calculating eigenvalues and eigenvectors.mp4
12.1 MB
Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/3. Self-supervised learning.mp4
12.0 MB
Building Computer Vision Applications with Python/7 - Morphological Modifications/2. Erosion and dilation.mp4
12.0 MB
Building Computer Vision Applications with Python/5 - Image Scaling/2. Downscaling example.mp4
11.9 MB
Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/2. Data vs. reasoning.mp4
11.9 MB
Building Computer Vision Applications with Python/4 - Filters/2. Average filters.mp4
11.9 MB
Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/1. Defining linear algebra.mp4
11.7 MB
Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/4. Gram–Schmidt process.mp4
11.6 MB
Building Computer Vision Applications with Python/3 - From Color to Black and White/1. Average grayscale.mp4
11.4 MB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/7. Solution Build a neural network.mp4
11.3 MB
Building Computer Vision Applications with Python/1 - Setting Up Your Environment/2. Testing your environment.mp4
11.1 MB
Building Computer Vision Applications with Python/3 - From Color to Black and White/3. Converting grayscale to black and white.mp4
11.0 MB
Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/2. The history of AI.mp4
10.9 MB
Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/1. Introduction to eigenvalues and eigenvectors.mp4
10.9 MB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/5. Train the neural network using Keras.mp4
10.8 MB
Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/1. Terms in reinforcement learning.mp4
10.7 MB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/2. Use case and determine evaluation metric.mp4
10.3 MB
Machine Learning Foundations Linear Algebra/2 - Vectors Basics/3. Coordinate system.mp4
10.3 MB
Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/2. Gaussian elimination and finding the inverse matrix.mp4
10.2 MB
Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/2. Types of matrices.mp4
10.1 MB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/7. Solution Manipulate some pictures.mp4
10.0 MB
Deep Learning Getting Started/4 - Deep Learning Example 1/4. Training and evaluation.mp4
9.9 MB
Deep Learning Getting Started/4 - Deep Learning Example 1/2. Input preprocessing.mp4
9.9 MB
Reinforcement Learning Foundations/4 - Temporal Difference Methods/3. SARSAMAX (Q-learning).mp4
9.6 MB
Building Computer Vision Applications with Python/7 - Morphological Modifications/4. Challenge Help a robot.mp4
9.5 MB
Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/4. How neural networks learn.mp4
9.3 MB
Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/3. Types of matrix transformation.mp4
9.3 MB
Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/1. Machine learning and neural networks.mp4
9.2 MB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/4. Resolution.mp4
9.2 MB
Machine Learning Foundations Linear Algebra/0 - Introduction/1. Introduction.mp4
9.0 MB
Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/4. A basic RL solution.mp4
9.0 MB
Building Computer Vision Applications with Python/4 - Filters/1. Convolution filters.mp4
8.9 MB
Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/3. Inverse and determinant.mp4
8.8 MB
Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/1. Matrices introduction.mp4
8.8 MB
Building Computer Vision Applications with Python/4 - Filters/4. Gaussian filters.mp4
8.6 MB
Hands-On PyTorch Machine Learning/2 - PyTorch Basics/3. Understand PyTorch NumPy Bridge.mp4
8.5 MB
Deep Learning Getting Started/4 - Deep Learning Example 1/3. Creating a deep learning model.mp4
8.5 MB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/2. Color encoding.mp4
8.3 MB
Building Computer Vision Applications with Python/7 - Morphological Modifications/5. Solution Help a robot.mp4
8.3 MB
Hands-On PyTorch Machine Learning/5 - Torchtext/1. Torchtext introduction.mp4
8.3 MB
Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/3. Transformer architecture.mp4
8.2 MB
Hands-On PyTorch Machine Learning/1 - Preparation/1. PyTorch overview.mp4
8.1 MB
Reinforcement Learning Foundations/3 - Monte Carlo Method/2. Exploration and exploitation.mp4
8.1 MB
Hands-On PyTorch Machine Learning/2 - PyTorch Basics/2. Understand PyTorch basic operations.mp4
7.9 MB
Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/1. Matrices changing basis.mp4
7.7 MB
Building Computer Vision Applications with Python/0 - Introduction/1. Computer vision under the hood.mp4
7.7 MB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/6. Challenge Manipulate some pictures.mp4
7.6 MB
Deep Learning Getting Started/5 - Deep Learning Example 2/2. Creating text representations.mp4
7.5 MB
Building Computer Vision Applications with Python/7 - Morphological Modifications/3. Open and close.mp4
7.5 MB
Artificial Intelligence Foundations Thinking Machines/0 - Introduction/1. Welcome.mp4
7.4 MB
Reinforcement Learning Foundations/4 - Temporal Difference Methods/4. Expected SARSA.mp4
7.4 MB
Hands-On PyTorch Machine Learning/2 - PyTorch Basics/1. Understand PyTorch tensors.mp4
7.4 MB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/1. Overfitting and underfitting Two common ANN problems.mp4
7.2 MB
Hands-On PyTorch Machine Learning/Ex_Files_Hands_On_PyTorch_ML.zip
7.2 MB
Reinforcement Learning Foundations/3 - Monte Carlo Method/4. First visit and every visit MC prediction.mp4
7.2 MB
Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/1. Multilayer perceptron.mp4
7.1 MB
Hands-On PyTorch Machine Learning/4 - Torchaudio/1. Torchaudio introduction.mp4
6.9 MB
Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/3. Orthogonal matrix.mp4
6.9 MB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/1. The Keras Sequential model.mp4
6.8 MB
Building Computer Vision Applications with Python/6 - Fun with Cuts/5. Solution Stitch two pictures together.mp4
6.7 MB
Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/4. Single-layer perceptron.mp4
6.7 MB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/3. How do you improve model performance.mp4
6.5 MB
Building Computer Vision Applications with Python/4 - Filters/7. Solution Convolution filters.mp4
6.5 MB
Building Computer Vision Applications with Python/3 - From Color to Black and White/2. Weighted grayscale.mp4
6.5 MB
Reinforcement Learning Foundations/6 - Conclusion/1. Your reinforcement learning journey.mp4
6.5 MB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/5. Rotations and flips.mp4
6.4 MB
Building Computer Vision Applications with Python/5 - Image Scaling/6. Solution Resize a picture.mp4
6.4 MB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/6. Solution Manually tune hyperparameters.mp4
6.4 MB
Deep Learning Getting Started/0 - Introduction/3. Setting up the environment.mp4
6.3 MB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/2. Hyperparameters and neural networks.mp4
6.3 MB
Deep Learning Getting Started/2 - Neural Network Architecture/1. The input layer.mp4
6.2 MB
Deep Learning Getting Started/6 - Deep Learning Exercise/1. Exercise problem statement.mp4
6.1 MB
Deep Learning Getting Started/1 - Introduction to Deep Learning/5. Artificial neural networks.mp4
6.1 MB
Deep Learning Getting Started/3 - Training a Neural Network/1. Setup and initialization.mp4
6.0 MB
Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/3. Transfer and activation functions.mp4
6.0 MB
Deep Learning Getting Started/2 - Neural Network Architecture/3. Weights and biases.mp4
5.9 MB
Deep Learning Getting Started/1 - Introduction to Deep Learning/2. Linear regression.mp4
5.8 MB
Hands-On PyTorch Machine Learning/2 - PyTorch Basics/4. Understand PyTorch autograd.mp4
5.7 MB
Machine Learning Foundations Linear Algebra/0 - Introduction/2. What you should know.mp4
5.6 MB
Deep Learning Getting Started/5 - Deep Learning Example 2/3. Building a spam model.mp4
5.5 MB
Deep Learning Getting Started/1 - Introduction to Deep Learning/6. Training an ANN.mp4
5.4 MB
Reinforcement Learning Foundations/4 - Temporal Difference Methods/1. The setting.mp4
5.4 MB
Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/2. Biological neural networks.mp4
5.3 MB
Hands-On PyTorch Machine Learning/2 - PyTorch Basics/5. Advanced PyTorch autograd.mp4
5.3 MB
Deep Learning Getting Started/0 - Introduction/2. Prerequisites for the course.mp4
5.1 MB
Deep Learning Getting Started/3 - Training a Neural Network/6. Batches and epochs.mp4
5.0 MB
Deep Learning Getting Started/3 - Training a Neural Network/4. Back propagation.mp4
5.0 MB
Building Computer Vision Applications with Python/4 - Filters/6. Challenge Convolution filters.mp4
5.0 MB
Deep Learning Getting Started/3 - Training a Neural Network/3. Measuring accuracy and error.mp4
5.0 MB
Deep Learning Getting Started/4 - Deep Learning Example 1/1. The Iris classification problem.mp4
4.9 MB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/3. Data checks and data preparation.mp4
4.9 MB
Deep Learning Getting Started/2 - Neural Network Architecture/2. Hidden layers.mp4
4.9 MB
Deep Learning Getting Started/4 - Deep Learning Example 1/6. Predictions with deep learning models.mp4
4.8 MB
Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/2. Layers Input, hidden, and output.mp4
4.8 MB
Reinforcement Learning Foundations/3 - Monte Carlo Method/6. Additional modifications.mp4
4.8 MB
Deep Learning Getting Started/1 - Introduction to Deep Learning/3. An analogy for deep learning.mp4
4.7 MB
Hands-On PyTorch Machine Learning/3 - Torchvision/2. Torchvision for video and image understanding.mp4
4.7 MB
Artificial Intelligence Foundations Neural Networks/0 - Introduction/1. Neural networks 101 Your path to AI brilliance.mp4
4.6 MB
Deep Learning Getting Started/3 - Training a Neural Network/10. Using available open-source models.mp4
4.5 MB
Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/1. Deep reinforcement learning.mp4
4.5 MB
Artificial Intelligence Foundations Thinking Machines/8 - Conclusion/1. Next steps.mp4
4.5 MB
Deep Learning Getting Started/3 - Training a Neural Network/9. Reusing existing network architectures.mp4
4.4 MB
Building Computer Vision Applications with Python/5 - Image Scaling/1. Image downscaling methods.mp4
4.4 MB
Building Computer Vision Applications with Python/3 - From Color to Black and White/6. Solution Removing color.mp4
4.4 MB
Deep Learning Getting Started/5 - Deep Learning Example 2/4. Predictions for text.mp4
4.3 MB
Deep Learning Getting Started/6 - Deep Learning Exercise/2. Preprocessing RCA data.mp4
4.2 MB
Deep Learning Getting Started/0 - Introduction/1. Getting started with deep learning.mp4
4.2 MB
Deep Learning Getting Started/2 - Neural Network Architecture/4. Activation functions.mp4
4.1 MB
Artificial Intelligence Foundations Neural Networks/0 - Introduction/3. How to use the challenge exercise files.mp4
3.9 MB
Deep Learning Getting Started/5 - Deep Learning Example 2/1. Spam classification problem.mp4
3.9 MB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/4. Data preprocessing.mp4
3.8 MB
Reinforcement Learning Foundations/0 - Introduction/1. Reinforcement learning in a nutshell.mp4
3.8 MB
Deep Learning Getting Started/6 - Deep Learning Exercise/3. Building the RCA model.mp4
3.8 MB
Building Computer Vision Applications with Python/6 - Fun with Cuts/4. Challenge Stitch two pictures together.mp4
3.8 MB
Hands-On PyTorch Machine Learning/1 - Preparation/3. PyTorch use case description.mp4
3.8 MB
Deep Learning Getting Started/3 - Training a Neural Network/8. An ANN model.mp4
3.7 MB
Building Computer Vision Applications with Python/5 - Image Scaling/3. Image upscaling methods.mp4
3.7 MB
Deep Learning Getting Started/2 - Neural Network Architecture/5. The output layer.mp4
3.6 MB
Reinforcement Learning Foundations/3 - Monte Carlo Method/1. The setting.mp4
3.4 MB
Deep Learning Getting Started/3 - Training a Neural Network/7. Validation and testing.mp4
3.4 MB
Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/3. Other RL algorithms.mp4
3.3 MB
Deep Learning Getting Started/4 - Deep Learning Example 1/5. Saving and loading models.mp4
3.2 MB
Deep Learning Getting Started/3 - Training a Neural Network/5. Gradient descent.mp4
3.2 MB
Building Computer Vision Applications with Python/5 - Image Scaling/5. Challenge Resize a picture.mp4
3.1 MB
Building Computer Vision Applications with Python/3 - From Color to Black and White/5. Challenge Removing color.mp4
3.0 MB
Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/3. Artificial neural networks.mp4
3.0 MB
Deep Learning Getting Started/3 - Training a Neural Network/2. Forward propagation.mp4
2.9 MB
Building Computer Vision Applications with Python/0 - Introduction/2. What you should know.mp4
2.9 MB
Deep Learning Getting Started/6 - Deep Learning Exercise/4. Predicting root causes with deep learning.mp4
2.8 MB
Deep Learning Getting Started/1 - Introduction to Deep Learning/1. What is deep learning.mp4
2.8 MB
Artificial Intelligence Foundations Neural Networks/6 - Conclusion/1. Next steps.mp4
2.7 MB
Deep Learning Getting Started/1 - Introduction to Deep Learning/4. The perceptron.mp4
2.7 MB
Hands-On PyTorch Machine Learning/0 - Introduction/1. Explore the capabilities of PyTorch.mp4
2.7 MB
Machine Learning Foundations Linear Algebra/8 - Conclusion/1. Next steps.mp4
2.6 MB
Reinforcement Learning Foundations/3 - Monte Carlo Method/3. Monte Carlo prediction.mp4
2.5 MB
Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/2. Temporal difference methods.mp4
2.4 MB
Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/3. Inverse reinforcement learning.mp4
2.3 MB
Building Computer Vision Applications with Python/1 - Setting Up Your Environment/1. Installing Anaconda and OpenCV.mp4
2.0 MB
Building Computer Vision Applications with Python/8 - Conclusion/1. Next steps.mp4
1.9 MB
Building Computer Vision Applications with Python/0 - Introduction/3. Using the exercise files.mp4
1.9 MB
Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/2. Multi-agent reinforcement learning.mp4
1.9 MB
Hands-On PyTorch Machine Learning/6 - Conclusion/1. Continuing your PyTorch learning process.mp4
1.8 MB
Artificial Intelligence Foundations Neural Networks/0 - Introduction/2. What you should know.mp4
1.7 MB
Deep Learning Getting Started/7 - Conclusion/1. Extending your deep learning education.mp4
1.6 MB
Reinforcement Learning Foundations/3 - Monte Carlo Method/5. Monte Carlo control.mp4
1.5 MB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/6. Challenge Build a neural network.mp4
1.3 MB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/5. Challenge Manually tune hyperparameters.mp4
1.2 MB
Deep Learning Getting Started/Ex_Files_Deep_Learning_Getting_Started.zip
105.4 kB
Machine Learning Foundations Linear Algebra/Ex_Files_ML_Foundations_Linear_Algebra.zip
34.1 kB
Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/1. Convolutional neural networks (CNN).srt
12.5 kB
Hands-On PyTorch Machine Learning/3 - Torchvision/1. Torchvision introduction.srt
12.3 kB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/4. Regularization techniques to improve overfitting models.srt
11.6 kB
Building Computer Vision Applications with Python/6 - Fun with Cuts/2. Stitching two images together.srt
10.1 kB
Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/2. Recurrent neural networks (RNN).srt
10.1 kB
Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/5. Regression.srt
9.1 kB
Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/3. Perceptrons.srt
8.7 kB
Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/1. Define general intelligence.srt
8.6 kB
Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/4. Plan AI.srt
8.6 kB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/3. Image file management.srt
8.6 kB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/5. Train the neural network using Keras.srt
8.6 kB
Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/1. Machine learning.srt
8.5 kB
Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/3. Strong vs. weak AI.srt
8.5 kB
Artificial Intelligence Foundations Thinking Machines/7 - Avoiding Pitfalls/1. Pitfalls.srt
8.4 kB
Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/2. Natural language processing.srt
8.4 kB
Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/1. Match patterns.srt
8.3 kB
Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/3. Unsupervised learning.srt
8.3 kB
Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/1. Robotics.srt
8.3 kB
Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/2. Data vs. reasoning.srt
8.2 kB
Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/2. Data science.srt
8.2 kB
Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/2. The history of AI.srt
8.1 kB
Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/2. Artificial neural networks.srt
8.0 kB
Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/2. Applications of linear algebra in ML.srt
7.8 kB
Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/1. Big data.srt
7.8 kB
Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/4. Backpropagation.srt
7.8 kB
Building Computer Vision Applications with Python/7 - Morphological Modifications/1. Why modify objects.srt
7.6 kB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/1. Overfitting and underfitting Two common ANN problems.srt
7.5 kB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/2. Use case and determine evaluation metric.srt
7.4 kB
Building Computer Vision Applications with Python/3 - From Color to Black and White/4. Adaptive thresholding.srt
7.3 kB
Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/3. Markov decision process.srt
7.1 kB
Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/3. The Internet of Things.srt
7.1 kB
Building Computer Vision Applications with Python/4 - Filters/3. Median filters.srt
7.0 kB
Machine Learning Foundations Linear Algebra/2 - Vectors Basics/1. Introduction to vectors.srt
7.0 kB
Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/4. How neural networks learn.srt
7.0 kB
Reinforcement Learning Foundations/4 - Temporal Difference Methods/2. SARSA.srt
7.0 kB
Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/2. A basic RL problem.srt
6.8 kB
Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/3. Changing basis of vectors.srt
6.6 kB
Building Computer Vision Applications with Python/4 - Filters/1. Convolution filters.srt
6.5 kB
Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/1. Solving linear equations using Gaussian elimination.srt
6.2 kB
Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/1. Machine learning and neural networks.srt
6.2 kB
Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/4. Google PageRank algorithm.srt
6.1 kB
Building Computer Vision Applications with Python/4 - Filters/5. Edge detection filters.srt
6.1 kB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/1. The Keras Sequential model.srt
6.0 kB
Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/1. Multilayer perceptron.srt
6.0 kB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/1. Image representation.srt
5.9 kB
Building Computer Vision Applications with Python/6 - Fun with Cuts/1. Image cuts.srt
5.9 kB
Hands-On PyTorch Machine Learning/1 - Preparation/1. PyTorch overview.srt
5.9 kB
Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/1. Generative AI.srt
5.9 kB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/3. How do you improve model performance.srt
5.8 kB
Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/3. Changing to the eigenbasis.srt
5.8 kB
Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/3. Transformer architecture.srt
5.7 kB
Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/2. Foundation models.srt
5.7 kB
Machine Learning Foundations Linear Algebra/2 - Vectors Basics/2. Vector arithmetic.srt
5.6 kB
Building Computer Vision Applications with Python/1 - Setting Up Your Environment/2. Testing your environment.srt
5.6 kB
Hands-On PyTorch Machine Learning/5 - Torchtext/2. Torchtext for translation.srt
5.6 kB
Hands-On PyTorch Machine Learning/1 - Preparation/2. PyTorch environment setup.srt
5.6 kB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/7. Solution Build a neural network.srt
5.6 kB
Hands-On PyTorch Machine Learning/1 - Preparation/4. PyTorch data exploration.srt
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Hands-On PyTorch Machine Learning/4 - Torchaudio/2. Torchaudio for audio understanding.srt
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Building Computer Vision Applications with Python/7 - Morphological Modifications/2. Erosion and dilation.srt
5.4 kB
Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/4. Single-layer perceptron.srt
5.4 kB
Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/3. Self-supervised learning.srt
5.3 kB
Building Computer Vision Applications with Python/3 - From Color to Black and White/1. Average grayscale.srt
5.2 kB
Hands-On PyTorch Machine Learning/5 - Torchtext/1. Torchtext introduction.srt
5.1 kB
Hands-On PyTorch Machine Learning/2 - PyTorch Basics/1. Understand PyTorch tensors.srt
5.1 kB
Building Computer Vision Applications with Python/5 - Image Scaling/4. Upscaling example.srt
5.1 kB
Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/3. Transfer and activation functions.srt
5.1 kB
Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/2. Scalar and vector projection.srt
5.0 kB
Hands-On PyTorch Machine Learning/2 - PyTorch Basics/3. Understand PyTorch NumPy Bridge.srt
5.0 kB
Deep Learning Getting Started/3 - Training a Neural Network/1. Setup and initialization.srt
4.9 kB
Hands-On PyTorch Machine Learning/4 - Torchaudio/1. Torchaudio introduction.srt
4.9 kB
Building Computer Vision Applications with Python/6 - Fun with Cuts/3. Cuts in panoramic photography.srt
4.9 kB
Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/1. Monte Carlo method.srt
4.9 kB
Building Computer Vision Applications with Python/5 - Image Scaling/2. Downscaling example.srt
4.7 kB
Deep Learning Getting Started/2 - Neural Network Architecture/1. The input layer.srt
4.7 kB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/4. Resolution.srt
4.6 kB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/2. Hyperparameters and neural networks.srt
4.6 kB
Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/1. Dot product of vectors.srt
4.5 kB
Deep Learning Getting Started/1 - Introduction to Deep Learning/3. An analogy for deep learning.srt
4.5 kB
Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/2. Gaussian elimination and finding the inverse matrix.srt
4.5 kB
Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/2. Calculating eigenvalues and eigenvectors.srt
4.5 kB
Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/3. Types of matrix transformation.srt
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Deep Learning Getting Started/4 - Deep Learning Example 1/4. Training and evaluation.srt
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Deep Learning Getting Started/1 - Introduction to Deep Learning/5. Artificial neural networks.srt
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Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/4. Composition or combination of matrix transformations.srt
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Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/2. Types of matrices.srt
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Deep Learning Getting Started/2 - Neural Network Architecture/3. Weights and biases.srt
4.3 kB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/2. Color encoding.srt
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Machine Learning Foundations Linear Algebra/2 - Vectors Basics/3. Coordinate system.srt
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Deep Learning Getting Started/4 - Deep Learning Example 1/2. Input preprocessing.srt
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Building Computer Vision Applications with Python/4 - Filters/2. Average filters.srt
4.3 kB
Reinforcement Learning Foundations/3 - Monte Carlo Method/6. Additional modifications.srt
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Deep Learning Getting Started/1 - Introduction to Deep Learning/2. Linear regression.srt
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Deep Learning Getting Started/0 - Introduction/2. Prerequisites for the course.srt
4.2 kB
Hands-On PyTorch Machine Learning/2 - PyTorch Basics/4. Understand PyTorch autograd.srt
4.2 kB
Building Computer Vision Applications with Python/3 - From Color to Black and White/3. Converting grayscale to black and white.srt
4.2 kB
Deep Learning Getting Started/1 - Introduction to Deep Learning/6. Training an ANN.srt
4.1 kB
Deep Learning Getting Started/4 - Deep Learning Example 1/3. Creating a deep learning model.srt
4.1 kB
Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/2. Layers Input, hidden, and output.srt
4.1 kB
Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/4. Basis, linear independence, and span.srt
4.1 kB
Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/1. Introduction to eigenvalues and eigenvectors.srt
4.1 kB
Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/4. Gram–Schmidt process.srt
4.1 kB
Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/3. Inverse and determinant.srt
4.0 kB
Deep Learning Getting Started/3 - Training a Neural Network/9. Reusing existing network architectures.srt
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Deep Learning Getting Started/3 - Training a Neural Network/6. Batches and epochs.srt
4.0 kB
Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/1. Matrices introduction.srt
3.9 kB
Deep Learning Getting Started/3 - Training a Neural Network/4. Back propagation.srt
3.9 kB
Deep Learning Getting Started/6 - Deep Learning Exercise/1. Exercise problem statement.srt
3.9 kB
Hands-On PyTorch Machine Learning/2 - PyTorch Basics/2. Understand PyTorch basic operations.srt
3.9 kB
Deep Learning Getting Started/3 - Training a Neural Network/3. Measuring accuracy and error.srt
3.8 kB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/7. Solution Manipulate some pictures.srt
3.8 kB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/3. Data checks and data preparation.srt
3.8 kB
Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/1. Terms in reinforcement learning.srt
3.8 kB
Deep Learning Getting Started/3 - Training a Neural Network/10. Using available open-source models.srt
3.8 kB
Building Computer Vision Applications with Python/2 - The Basics of Image Processing/6. Challenge Manipulate some pictures.srt
3.7 kB
Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/2. Transforming to the new basis.srt
3.7 kB
Deep Learning Getting Started/0 - Introduction/3. Setting up the environment.srt
3.7 kB
Hands-On PyTorch Machine Learning/1 - Preparation/3. PyTorch use case description.srt
3.7 kB
Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/4. A basic RL solution.srt
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Deep Learning Getting Started/2 - Neural Network Architecture/4. Activation functions.srt
3.6 kB
Reinforcement Learning Foundations/3 - Monte Carlo Method/2. Exploration and exploitation.srt
3.6 kB
Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/2. Biological neural networks.srt
3.6 kB
Building Computer Vision Applications with Python/7 - Morphological Modifications/4. Challenge Help a robot.srt
3.5 kB
Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/1. Defining linear algebra.srt
3.5 kB
Artificial Intelligence Foundations Thinking Machines/0 - Introduction/1. Welcome.srt
3.4 kB
Building Computer Vision Applications with Python/5 - Image Scaling/1. Image downscaling methods.srt
3.3 kB
Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/1. Matrices changing basis.srt
3.3 kB
Reinforcement Learning Foundations/4 - Temporal Difference Methods/3. SARSAMAX (Q-learning).srt
3.3 kB
Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/3. Orthogonal matrix.srt
3.3 kB
Hands-On PyTorch Machine Learning/2 - PyTorch Basics/5. Advanced PyTorch autograd.srt
3.2 kB
Deep Learning Getting Started/3 - Training a Neural Network/8. An ANN model.srt
3.1 kB
Deep Learning Getting Started/5 - Deep Learning Example 2/2. Creating text representations.srt
3.1 kB
Building Computer Vision Applications with Python/4 - Filters/4. Gaussian filters.srt
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Building Computer Vision Applications with Python/2 - The Basics of Image Processing/5. Rotations and flips.srt
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Deep Learning Getting Started/5 - Deep Learning Example 2/1. Spam classification problem.srt
2.9 kB
Deep Learning Getting Started/2 - Neural Network Architecture/2. Hidden layers.srt
2.9 kB
Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/4. Data preprocessing.srt
2.9 kB
Reinforcement Learning Foundations/6 - Conclusion/1. Your reinforcement learning journey.srt
2.9 kB
Building Computer Vision Applications with Python/7 - Morphological Modifications/3. Open and close.srt
2.8 kB
Building Computer Vision Applications with Python/5 - Image Scaling/3. Image upscaling methods.srt
2.8 kB
Deep Learning Getting Started/2 - Neural Network Architecture/5. The output layer.srt
2.8 kB
Deep Learning Getting Started/1 - Introduction to Deep Learning/1. What is deep learning.srt
2.8 kB
Reinforcement Learning Foundations/3 - Monte Carlo Method/4. First visit and every visit MC prediction.srt
2.8 kB
Reinforcement Learning Foundations/3 - Monte Carlo Method/3. Monte Carlo prediction.srt
2.7 kB
Artificial Intelligence Foundations Neural Networks/6 - Conclusion/1. Next steps.srt
2.7 kB
Deep Learning Getting Started/1 - Introduction to Deep Learning/4. The perceptron.srt
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Deep Learning Getting Started/3 - Training a Neural Network/7. Validation and testing.srt
2.7 kB
Reinforcement Learning Foundations/4 - Temporal Difference Methods/4. Expected SARSA.srt
2.6 kB
Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/3. Artificial neural networks.srt
2.5 kB
Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/6. Solution Manually tune hyperparameters.srt
2.5 kB
Deep Learning Getting Started/4 - Deep Learning Example 1/6. Predictions with deep learning models.srt
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Deep Learning Getting Started/3 - Training a Neural Network/5. Gradient descent.srt
2.4 kB
Deep Learning Getting Started/5 - Deep Learning Example 2/4. Predictions for text.srt
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Deep Learning Getting Started/4 - Deep Learning Example 1/1. The Iris classification problem.srt
2.3 kB
Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/1. Deep reinforcement learning.srt
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Building Computer Vision Applications with Python/0 - Introduction/2. What you should know.srt
2.2 kB
Deep Learning Getting Started/3 - Training a Neural Network/2. Forward propagation.srt
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Reinforcement Learning Foundations/3 - Monte Carlo Method/1. The setting.srt
2.2 kB
Building Computer Vision Applications with Python/0 - Introduction/1. Computer vision under the hood.srt
2.1 kB
Artificial Intelligence Foundations Neural Networks/0 - Introduction/3. How to use the challenge exercise files.srt
2.1 kB
Deep Learning Getting Started/5 - Deep Learning Example 2/3. Building a spam model.srt
2.0 kB
Building Computer Vision Applications with Python/7 - Morphological Modifications/5. Solution Help a robot.srt
2.0 kB
Deep Learning Getting Started/4 - Deep Learning Example 1/5. Saving and loading models.srt
2.0 kB
Building Computer Vision Applications with Python/4 - Filters/6. Challenge Convolution filters.srt
2.0 kB
Building Computer Vision Applications with Python/3 - From Color to Black and White/2. Weighted grayscale.srt
2.0 kB
Hands-On PyTorch Machine Learning/3 - Torchvision/2. Torchvision for video and image understanding.srt
1.9 kB
Building Computer Vision Applications with Python/6 - Fun with Cuts/5. Solution Stitch two pictures together.srt
1.9 kB
Hands-On PyTorch Machine Learning/6 - Conclusion/1. Continuing your PyTorch learning process.srt
1.9 kB
Reinforcement Learning Foundations/4 - Temporal Difference Methods/1. The setting.srt
1.9 kB
Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/2. Temporal difference methods.srt
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Building Computer Vision Applications with Python/5 - Image Scaling/6. Solution Resize a picture.srt
1.8 kB
Artificial Intelligence Foundations Thinking Machines/8 - Conclusion/1. Next steps.srt
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Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/3. Inverse reinforcement learning.srt
1.8 kB
Building Computer Vision Applications with Python/6 - Fun with Cuts/4. Challenge Stitch two pictures together.srt
1.8 kB
Building Computer Vision Applications with Python/4 - Filters/7. Solution Convolution filters.srt
1.7 kB
Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/2. Multi-agent reinforcement learning.srt
1.7 kB
Building Computer Vision Applications with Python/1 - Setting Up Your Environment/1. Installing Anaconda and OpenCV.srt
1.7 kB
Machine Learning Foundations Linear Algebra/0 - Introduction/2. What you should know.srt
1.7 kB
Machine Learning Foundations Linear Algebra/0 - Introduction/1. Introduction.srt
1.6 kB
Deep Learning Getting Started/6 - Deep Learning Exercise/2. Preprocessing RCA data.srt
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Deep Learning Getting Started/0 - Introduction/1. Getting started with deep learning.srt
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Reinforcement Learning Foundations/0 - Introduction/1. Reinforcement learning in a nutshell.srt
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Building Computer Vision Applications with Python/3 - From Color to Black and White/6. Solution Removing color.srt
1.5 kB
Building Computer Vision Applications with Python/0 - Introduction/3. Using the exercise files.srt
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Reinforcement Learning Foundations/3 - Monte Carlo Method/5. Monte Carlo control.srt
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Building Computer Vision Applications with Python/3 - From Color to Black and White/5. Challenge Removing color.srt
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Building Computer Vision Applications with Python/5 - Image Scaling/5. Challenge Resize a picture.srt
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Hands-On PyTorch Machine Learning/0 - Introduction/1. Explore the capabilities of PyTorch.srt
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Artificial Intelligence Foundations Neural Networks/0 - Introduction/1. Neural networks 101 Your path to AI brilliance.srt
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Artificial Intelligence Foundations Thinking Machines/description.html
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Artificial Intelligence Foundations Neural Networks/description.html
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Deep Learning Getting Started/6 - Deep Learning Exercise/3. Building the RCA model.srt
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Deep Learning Getting Started/description.html
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Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/6. Challenge Build a neural network.srt
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Building Computer Vision Applications with Python/8 - Conclusion/1. Next steps.srt
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Machine Learning Foundations Linear Algebra/8 - Conclusion/1. Next steps.srt
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Building Computer Vision Applications with Python/description.html
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Hands-On PyTorch Machine Learning/description.html
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Reinforcement Learning Foundations/description.html
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