[LinkedIn Learning] Getting Started with AI and Machine Learning - Complete 7 Courses

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Size

$10 ChatGPT for 1 Year & More.txt

252 B

Artificial Intelligence Foundations Neural Networks/0 - Introduction/2. What you should know.srt

908 B

Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/3. Other RL algorithms.srt

916 B

Deep Learning Getting Started/7 - Conclusion/1. Extending your deep learning education.srt

1.0 kB

Reinforcement Learning Foundations/description.html

1.0 kB

Hands-On PyTorch Machine Learning/description.html

1.1 kB

Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/5. Challenge Manually tune hyperparameters.srt

1.1 kB

Machine Learning Foundations Linear Algebra/description.html

1.1 kB

Building Computer Vision Applications with Python/description.html

1.1 kB

Machine Learning Foundations Linear Algebra/8 - Conclusion/1. Next steps.srt

1.2 kB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/6. Challenge Build a neural network.srt

1.2 kB

Building Computer Vision Applications with Python/8 - Conclusion/1. Next steps.srt

1.2 kB

Deep Learning Getting Started/description.html

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Deep Learning Getting Started/6 - Deep Learning Exercise/3. Building the RCA model.srt

1.2 kB

Artificial Intelligence Foundations Neural Networks/description.html

1.2 kB

Artificial Intelligence Foundations Thinking Machines/description.html

1.3 kB

Artificial Intelligence Foundations Neural Networks/0 - Introduction/1. Neural networks 101 Your path to AI brilliance.srt

1.3 kB

Hands-On PyTorch Machine Learning/0 - Introduction/1. Explore the capabilities of PyTorch.srt

1.4 kB

Building Computer Vision Applications with Python/5 - Image Scaling/5. Challenge Resize a picture.srt

1.4 kB

Building Computer Vision Applications with Python/3 - From Color to Black and White/5. Challenge Removing color.srt

1.4 kB

Reinforcement Learning Foundations/3 - Monte Carlo Method/5. Monte Carlo control.srt

1.4 kB

Building Computer Vision Applications with Python/0 - Introduction/3. Using the exercise files.srt

1.4 kB

Building Computer Vision Applications with Python/3 - From Color to Black and White/6. Solution Removing color.srt

1.5 kB

Reinforcement Learning Foundations/0 - Introduction/1. Reinforcement learning in a nutshell.srt

1.5 kB

Deep Learning Getting Started/6 - Deep Learning Exercise/4. Predicting root causes with deep learning.srt

1.5 kB

Deep Learning Getting Started/0 - Introduction/1. Getting started with deep learning.srt

1.5 kB

Deep Learning Getting Started/6 - Deep Learning Exercise/2. Preprocessing RCA data.srt

1.5 kB

Machine Learning Foundations Linear Algebra/0 - Introduction/1. Introduction.srt

1.5 kB

Machine Learning Foundations Linear Algebra/0 - Introduction/2. What you should know.srt

1.6 kB

Building Computer Vision Applications with Python/1 - Setting Up Your Environment/1. Installing Anaconda and OpenCV.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/4 - Filters/7. Solution Convolution filters.srt

1.7 kB

Building Computer Vision Applications with Python/6 - Fun with Cuts/4. Challenge Stitch two pictures together.srt

1.7 kB

Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/3. Inverse reinforcement learning.srt

1.8 kB

Artificial Intelligence Foundations Thinking Machines/8 - Conclusion/1. Next steps.srt

1.8 kB

Building Computer Vision Applications with Python/5 - Image Scaling/6. Solution Resize a picture.srt

1.8 kB

Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/2. Temporal difference methods.srt

1.8 kB

Reinforcement Learning Foundations/4 - Temporal Difference Methods/1. The setting.srt

1.8 kB

Hands-On PyTorch Machine Learning/6 - Conclusion/1. Continuing your PyTorch learning process.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/3 - Torchvision/2. Torchvision for video and image understanding.srt

1.9 kB

Building Computer Vision Applications with Python/3 - From Color to Black and White/2. Weighted grayscale.srt

1.9 kB

Building Computer Vision Applications with Python/4 - Filters/6. Challenge Convolution filters.srt

1.9 kB

Deep Learning Getting Started/4 - Deep Learning Example 1/5. Saving and loading models.srt

1.9 kB

Building Computer Vision Applications with Python/7 - Morphological Modifications/5. Solution Help a robot.srt

2.0 kB

Deep Learning Getting Started/5 - Deep Learning Example 2/3. Building a spam model.srt

2.0 kB

Artificial Intelligence Foundations Neural Networks/0 - Introduction/3. How to use the challenge exercise files.srt

2.1 kB

Building Computer Vision Applications with Python/0 - Introduction/1. Computer vision under the hood.srt

2.1 kB

Reinforcement Learning Foundations/3 - Monte Carlo Method/1. The setting.srt

2.1 kB

Deep Learning Getting Started/3 - Training a Neural Network/2. Forward propagation.srt

2.1 kB

Building Computer Vision Applications with Python/0 - Introduction/2. What you should know.srt

2.1 kB

Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/1. Deep reinforcement learning.srt

2.2 kB

Deep Learning Getting Started/4 - Deep Learning Example 1/1. The Iris classification problem.srt

2.2 kB

Deep Learning Getting Started/5 - Deep Learning Example 2/4. Predictions for text.srt

2.2 kB

Deep Learning Getting Started/3 - Training a Neural Network/5. Gradient descent.srt

2.4 kB

Deep Learning Getting Started/4 - Deep Learning Example 1/6. Predictions with deep learning models.srt

2.4 kB

Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/6. Solution Manually tune hyperparameters.srt

2.5 kB

Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/3. Artificial neural networks.srt

2.5 kB

Reinforcement Learning Foundations/4 - Temporal Difference Methods/4. Expected SARSA.srt

2.5 kB

Deep Learning Getting Started/3 - Training a Neural Network/7. Validation and testing.srt

2.6 kB

Deep Learning Getting Started/1 - Introduction to Deep Learning/4. The perceptron.srt

2.6 kB

Artificial Intelligence Foundations Neural Networks/6 - Conclusion/1. Next steps.srt

2.6 kB

Reinforcement Learning Foundations/3 - Monte Carlo Method/3. Monte Carlo prediction.srt

2.7 kB

Reinforcement Learning Foundations/3 - Monte Carlo Method/4. First visit and every visit MC prediction.srt

2.7 kB

Deep Learning Getting Started/1 - Introduction to Deep Learning/1. What is deep learning.srt

2.7 kB

Deep Learning Getting Started/2 - Neural Network Architecture/5. The output layer.srt

2.7 kB

Building Computer Vision Applications with Python/5 - Image Scaling/3. Image upscaling methods.srt

2.8 kB

Building Computer Vision Applications with Python/7 - Morphological Modifications/3. Open and close.srt

2.8 kB

Reinforcement Learning Foundations/6 - Conclusion/1. Your reinforcement learning journey.srt

2.8 kB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/4. Data preprocessing.srt

2.8 kB

Deep Learning Getting Started/2 - Neural Network Architecture/2. Hidden layers.srt

2.8 kB

Deep Learning Getting Started/5 - Deep Learning Example 2/1. Spam classification problem.srt

2.8 kB

Building Computer Vision Applications with Python/2 - The Basics of Image Processing/5. Rotations and flips.srt

2.9 kB

Building Computer Vision Applications with Python/4 - Filters/4. Gaussian filters.srt

2.9 kB

Deep Learning Getting Started/3 - Training a Neural Network/8. An ANN model.srt

3.0 kB

Deep Learning Getting Started/5 - Deep Learning Example 2/2. Creating text representations.srt

3.0 kB

Hands-On PyTorch Machine Learning/2 - PyTorch Basics/5. Advanced PyTorch autograd.srt

3.1 kB

Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/3. Orthogonal matrix.srt

3.2 kB

Reinforcement Learning Foundations/4 - Temporal Difference Methods/3. SARSAMAX (Q-learning).srt

3.2 kB

Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/1. Matrices changing basis.srt

3.2 kB

Building Computer Vision Applications with Python/5 - Image Scaling/1. Image downscaling methods.srt

3.3 kB

Artificial Intelligence Foundations Thinking Machines/0 - Introduction/1. Welcome.srt

3.3 kB

Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/1. Defining linear algebra.srt

3.5 kB

Building Computer Vision Applications with Python/7 - Morphological Modifications/4. Challenge Help a robot.srt

3.5 kB

Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/2. Biological neural networks.srt

3.5 kB

Reinforcement Learning Foundations/3 - Monte Carlo Method/2. Exploration and exploitation.srt

3.5 kB

Deep Learning Getting Started/2 - Neural Network Architecture/4. Activation functions.srt

3.5 kB

Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/4. A basic RL solution.srt

3.5 kB

Hands-On PyTorch Machine Learning/1 - Preparation/3. PyTorch use case description.srt

3.6 kB

Deep Learning Getting Started/0 - Introduction/3. Setting up the environment.srt

3.6 kB

Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/2. Transforming to the new basis.srt

3.6 kB

Building Computer Vision Applications with Python/2 - The Basics of Image Processing/6. Challenge Manipulate some pictures.srt

3.7 kB

Deep Learning Getting Started/3 - Training a Neural Network/10. Using available open-source models.srt

3.7 kB

Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/1. Terms in reinforcement learning.srt

3.7 kB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/3. Data checks and data preparation.srt

3.7 kB

Building Computer Vision Applications with Python/2 - The Basics of Image Processing/7. Solution Manipulate some pictures.srt

3.7 kB

Deep Learning Getting Started/3 - Training a Neural Network/3. Measuring accuracy and error.srt

3.8 kB

Hands-On PyTorch Machine Learning/2 - PyTorch Basics/2. Understand PyTorch basic operations.srt

3.8 kB

Deep Learning Getting Started/6 - Deep Learning Exercise/1. Exercise problem statement.srt

3.8 kB

Deep Learning Getting Started/3 - Training a Neural Network/4. Back propagation.srt

3.8 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/6. Batches and epochs.srt

3.9 kB

Deep Learning Getting Started/3 - Training a Neural Network/9. Reusing existing network architectures.srt

3.9 kB

Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/3. Inverse and determinant.srt

3.9 kB

Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/4. Gram–Schmidt process.srt

4.0 kB

Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/1. Introduction to eigenvalues and eigenvectors.srt

4.0 kB

Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/4. Basis, linear independence, and span.srt

4.0 kB

Deep Learning Getting Started/4 - Deep Learning Example 1/3. Creating a deep learning model.srt

4.0 kB

Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/2. Layers Input, hidden, and output.srt

4.0 kB

Deep Learning Getting Started/1 - Introduction to Deep Learning/6. Training an ANN.srt

4.0 kB

Building Computer Vision Applications with Python/3 - From Color to Black and White/3. Converting grayscale to black and white.srt

4.1 kB

Hands-On PyTorch Machine Learning/2 - PyTorch Basics/4. Understand PyTorch autograd.srt

4.1 kB

Deep Learning Getting Started/0 - Introduction/2. Prerequisites for the course.srt

4.1 kB

Deep Learning Getting Started/1 - Introduction to Deep Learning/2. Linear regression.srt

4.2 kB

Reinforcement Learning Foundations/3 - Monte Carlo Method/6. Additional modifications.srt

4.2 kB

Building Computer Vision Applications with Python/4 - Filters/2. Average filters.srt

4.2 kB

Deep Learning Getting Started/4 - Deep Learning Example 1/2. Input preprocessing.srt

4.2 kB

Machine Learning Foundations Linear Algebra/2 - Vectors Basics/3. Coordinate system.srt

4.2 kB

Building Computer Vision Applications with Python/2 - The Basics of Image Processing/2. Color encoding.srt

4.2 kB

Deep Learning Getting Started/2 - Neural Network Architecture/3. Weights and biases.srt

4.2 kB

Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/2. Types of matrices.srt

4.3 kB

Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/4. Composition or combination of matrix transformations.srt

4.3 kB

Deep Learning Getting Started/1 - Introduction to Deep Learning/5. Artificial neural networks.srt

4.3 kB

Deep Learning Getting Started/4 - Deep Learning Example 1/4. Training and evaluation.srt

4.3 kB

Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/3. Types of matrix transformation.srt

4.3 kB

Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/2. Calculating eigenvalues and eigenvectors.srt

4.4 kB

Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/2. Gaussian elimination and finding the inverse matrix.srt

4.4 kB

Deep Learning Getting Started/1 - Introduction to Deep Learning/3. An analogy for deep learning.srt

4.4 kB

Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/1. Dot product of vectors.srt

4.4 kB

Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/2. Hyperparameters and neural networks.srt

4.5 kB

Building Computer Vision Applications with Python/2 - The Basics of Image Processing/4. Resolution.srt

4.5 kB

Deep Learning Getting Started/2 - Neural Network Architecture/1. The input layer.srt

4.6 kB

Building Computer Vision Applications with Python/5 - Image Scaling/2. Downscaling example.srt

4.6 kB

Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/1. Monte Carlo method.srt

4.7 kB

Building Computer Vision Applications with Python/6 - Fun with Cuts/3. Cuts in panoramic photography.srt

4.8 kB

Hands-On PyTorch Machine Learning/4 - Torchaudio/1. Torchaudio introduction.srt

4.8 kB

Deep Learning Getting Started/3 - Training a Neural Network/1. Setup and initialization.srt

4.8 kB

Hands-On PyTorch Machine Learning/2 - PyTorch Basics/3. Understand PyTorch NumPy Bridge.srt

4.8 kB

Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/2. Scalar and vector projection.srt

4.9 kB

Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/3. Transfer and activation functions.srt

5.0 kB

Building Computer Vision Applications with Python/5 - Image Scaling/4. Upscaling example.srt

5.0 kB

Hands-On PyTorch Machine Learning/2 - PyTorch Basics/1. Understand PyTorch tensors.srt

5.0 kB

Hands-On PyTorch Machine Learning/5 - Torchtext/1. Torchtext introduction.srt

5.0 kB

Building Computer Vision Applications with Python/3 - From Color to Black and White/1. Average grayscale.srt

5.0 kB

Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/3. Self-supervised learning.srt

5.2 kB

Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/4. Single-layer perceptron.srt

5.3 kB

Building Computer Vision Applications with Python/7 - Morphological Modifications/2. Erosion and dilation.srt

5.3 kB

Hands-On PyTorch Machine Learning/4 - Torchaudio/2. Torchaudio for audio understanding.srt

5.4 kB

Hands-On PyTorch Machine Learning/1 - Preparation/4. PyTorch data exploration.srt

5.5 kB

Hands-On PyTorch Machine Learning/1 - Preparation/2. PyTorch environment setup.srt

5.5 kB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/7. Solution Build a neural network.srt

5.5 kB

Hands-On PyTorch Machine Learning/5 - Torchtext/2. Torchtext for translation.srt

5.5 kB

Building Computer Vision Applications with Python/1 - Setting Up Your Environment/2. Testing your environment.srt

5.5 kB

Machine Learning Foundations Linear Algebra/2 - Vectors Basics/2. Vector arithmetic.srt

5.5 kB

Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/2. Foundation models.srt

5.5 kB

Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/3. Transformer architecture.srt

5.6 kB

Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/3. Changing to the eigenbasis.srt

5.7 kB

Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/3. How do you improve model performance.srt

5.7 kB

Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/1. Generative AI.srt

5.8 kB

Hands-On PyTorch Machine Learning/1 - Preparation/1. PyTorch overview.srt

5.8 kB

Building Computer Vision Applications with Python/6 - Fun with Cuts/1. Image cuts.srt

5.8 kB

Building Computer Vision Applications with Python/2 - The Basics of Image Processing/1. Image representation.srt

5.8 kB

Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/1. Multilayer perceptron.srt

5.8 kB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/1. The Keras Sequential model.srt

5.9 kB

Building Computer Vision Applications with Python/4 - Filters/5. Edge detection filters.srt

6.0 kB

Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/4. Google PageRank algorithm.srt

6.0 kB

Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/1. Machine learning and neural networks.srt

6.0 kB

Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/1. Solving linear equations using Gaussian elimination.srt

6.1 kB

Building Computer Vision Applications with Python/4 - Filters/1. Convolution filters.srt

6.3 kB

Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/3. Changing basis of vectors.srt

6.4 kB

Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/2. A basic RL problem.srt

6.7 kB

Reinforcement Learning Foundations/4 - Temporal Difference Methods/2. SARSA.srt

6.8 kB

Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/4. How neural networks learn.srt

6.8 kB

Machine Learning Foundations Linear Algebra/2 - Vectors Basics/1. Introduction to vectors.srt

6.9 kB

Building Computer Vision Applications with Python/4 - Filters/3. Median filters.srt

6.9 kB

Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/3. The Internet of Things.srt

6.9 kB

Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/3. Markov decision process.srt

7.0 kB

Building Computer Vision Applications with Python/3 - From Color to Black and White/4. Adaptive thresholding.srt

7.2 kB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/2. Use case and determine evaluation metric.srt

7.2 kB

Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/1. Overfitting and underfitting Two common ANN problems.srt

7.4 kB

Building Computer Vision Applications with Python/7 - Morphological Modifications/1. Why modify objects.srt

7.4 kB

Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/4. Backpropagation.srt

7.6 kB

Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/1. Big data.srt

7.6 kB

Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/2. Applications of linear algebra in ML.srt

7.6 kB

Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/2. Artificial neural networks.srt

7.9 kB

Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/2. The history of AI.srt

7.9 kB

Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/2. Data science.srt

8.0 kB

Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/2. Data vs. reasoning.srt

8.1 kB

Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/1. Robotics.srt

8.1 kB

Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/3. Unsupervised learning.srt

8.1 kB

Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/1. Match patterns.srt

8.1 kB

Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/2. Natural language processing.srt

8.2 kB

Artificial Intelligence Foundations Thinking Machines/7 - Avoiding Pitfalls/1. Pitfalls.srt

8.2 kB

Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/3. Strong vs. weak AI.srt

8.3 kB

Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/1. Machine learning.srt

8.3 kB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/5. Train the neural network using Keras.srt

8.4 kB

Building Computer Vision Applications with Python/2 - The Basics of Image Processing/3. Image file management.srt

8.4 kB

Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/4. Plan AI.srt

8.4 kB

Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/1. Define general intelligence.srt

8.4 kB

Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/3. Perceptrons.srt

8.5 kB

Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/5. Regression.srt

8.9 kB

Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/2. Recurrent neural networks (RNN).srt

9.8 kB

Building Computer Vision Applications with Python/6 - Fun with Cuts/2. Stitching two images together.srt

9.9 kB

Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/4. Regularization techniques to improve overfitting models.srt

11 kB

Hands-On PyTorch Machine Learning/3 - Torchvision/1. Torchvision introduction.srt

12 kB

Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/1. Convolutional neural networks (CNN).srt

12 kB

Machine Learning Foundations Linear Algebra/Ex_Files_ML_Foundations_Linear_Algebra.zip

33 kB

Deep Learning Getting Started/Ex_Files_Deep_Learning_Getting_Started.zip

103 kB

Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/5. Challenge Manually tune hyperparameters.mp4

1.1 MB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/6. Challenge Build a neural network.mp4

1.3 MB

Reinforcement Learning Foundations/3 - Monte Carlo Method/5. Monte Carlo control.mp4

1.4 MB

Deep Learning Getting Started/7 - Conclusion/1. Extending your deep learning education.mp4

1.5 MB

Artificial Intelligence Foundations Neural Networks/0 - Introduction/2. What you should know.mp4

1.6 MB

Hands-On PyTorch Machine Learning/6 - Conclusion/1. Continuing your PyTorch learning process.mp4

1.7 MB

Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/2. Multi-agent reinforcement learning.mp4

1.8 MB

Building Computer Vision Applications with Python/0 - Introduction/3. Using the exercise files.mp4

1.8 MB

Building Computer Vision Applications with Python/8 - Conclusion/1. Next steps.mp4

1.8 MB

Building Computer Vision Applications with Python/1 - Setting Up Your Environment/1. Installing Anaconda and OpenCV.mp4

1.9 MB

Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/3. Inverse reinforcement learning.mp4

2.2 MB

Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/2. Temporal difference methods.mp4

2.3 MB

Reinforcement Learning Foundations/3 - Monte Carlo Method/3. Monte Carlo prediction.mp4

2.4 MB

Machine Learning Foundations Linear Algebra/8 - Conclusion/1. Next steps.mp4

2.5 MB

Hands-On PyTorch Machine Learning/0 - Introduction/1. Explore the capabilities of PyTorch.mp4

2.5 MB

Deep Learning Getting Started/1 - Introduction to Deep Learning/4. The perceptron.mp4

2.6 MB

Artificial Intelligence Foundations Neural Networks/6 - Conclusion/1. Next steps.mp4

2.6 MB

Deep Learning Getting Started/1 - Introduction to Deep Learning/1. What is deep learning.mp4

2.6 MB

Deep Learning Getting Started/6 - Deep Learning Exercise/4. Predicting root causes with deep learning.mp4

2.7 MB

Building Computer Vision Applications with Python/0 - Introduction/2. What you should know.mp4

2.7 MB

Deep Learning Getting Started/3 - Training a Neural Network/2. Forward propagation.mp4

2.8 MB

Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/3. Artificial neural networks.mp4

2.9 MB

Building Computer Vision Applications with Python/3 - From Color to Black and White/5. Challenge Removing color.mp4

2.9 MB

Building Computer Vision Applications with Python/5 - Image Scaling/5. Challenge Resize a picture.mp4

2.9 MB

Deep Learning Getting Started/3 - Training a Neural Network/5. Gradient descent.mp4

3.0 MB

Deep Learning Getting Started/4 - Deep Learning Example 1/5. Saving and loading models.mp4

3.0 MB

Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/3. Other RL algorithms.mp4

3.2 MB

Deep Learning Getting Started/3 - Training a Neural Network/7. Validation and testing.mp4

3.2 MB

Reinforcement Learning Foundations/3 - Monte Carlo Method/1. The setting.mp4

3.2 MB

Deep Learning Getting Started/2 - Neural Network Architecture/5. The output layer.mp4

3.4 MB

Building Computer Vision Applications with Python/5 - Image Scaling/3. Image upscaling methods.mp4

3.5 MB

Deep Learning Getting Started/3 - Training a Neural Network/8. An ANN model.mp4

3.5 MB

Hands-On PyTorch Machine Learning/1 - Preparation/3. PyTorch use case description.mp4

3.6 MB

Building Computer Vision Applications with Python/6 - Fun with Cuts/4. Challenge Stitch two pictures together.mp4

3.6 MB

Deep Learning Getting Started/6 - Deep Learning Exercise/3. Building the RCA model.mp4

3.6 MB

Reinforcement Learning Foundations/0 - Introduction/1. Reinforcement learning in a nutshell.mp4

3.7 MB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/4. Data preprocessing.mp4

3.7 MB

Deep Learning Getting Started/5 - Deep Learning Example 2/1. Spam classification problem.mp4

3.7 MB

Artificial Intelligence Foundations Neural Networks/0 - Introduction/3. How to use the challenge exercise files.mp4

3.7 MB

Deep Learning Getting Started/2 - Neural Network Architecture/4. Activation functions.mp4

3.9 MB

Deep Learning Getting Started/0 - Introduction/1. Getting started with deep learning.mp4

4.0 MB

Deep Learning Getting Started/6 - Deep Learning Exercise/2. Preprocessing RCA data.mp4

4.0 MB

Deep Learning Getting Started/5 - Deep Learning Example 2/4. Predictions for text.mp4

4.1 MB

Building Computer Vision Applications with Python/3 - From Color to Black and White/6. Solution Removing color.mp4

4.2 MB

Building Computer Vision Applications with Python/5 - Image Scaling/1. Image downscaling methods.mp4

4.2 MB

Deep Learning Getting Started/3 - Training a Neural Network/9. Reusing existing network architectures.mp4

4.2 MB

Artificial Intelligence Foundations Thinking Machines/8 - Conclusion/1. Next steps.mp4

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Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/1. Deep reinforcement learning.mp4

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Deep Learning Getting Started/3 - Training a Neural Network/10. Using available open-source models.mp4

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Artificial Intelligence Foundations Neural Networks/0 - Introduction/1. Neural networks 101 Your path to AI brilliance.mp4

4.4 MB

Hands-On PyTorch Machine Learning/3 - Torchvision/2. Torchvision for video and image understanding.mp4

4.5 MB

Deep Learning Getting Started/1 - Introduction to Deep Learning/3. An analogy for deep learning.mp4

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Reinforcement Learning Foundations/3 - Monte Carlo Method/6. Additional modifications.mp4

4.5 MB

Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/2. Layers Input, hidden, and output.mp4

4.5 MB

Deep Learning Getting Started/4 - Deep Learning Example 1/6. Predictions with deep learning models.mp4

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Deep Learning Getting Started/2 - Neural Network Architecture/2. Hidden layers.mp4

4.6 MB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/3. Data checks and data preparation.mp4

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Deep Learning Getting Started/4 - Deep Learning Example 1/1. The Iris classification problem.mp4

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Deep Learning Getting Started/3 - Training a Neural Network/3. Measuring accuracy and error.mp4

4.7 MB

Building Computer Vision Applications with Python/4 - Filters/6. Challenge Convolution filters.mp4

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Deep Learning Getting Started/3 - Training a Neural Network/4. Back propagation.mp4

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Deep Learning Getting Started/3 - Training a Neural Network/6. Batches and epochs.mp4

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Deep Learning Getting Started/0 - Introduction/2. Prerequisites for the course.mp4

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Hands-On PyTorch Machine Learning/2 - PyTorch Basics/5. Advanced PyTorch autograd.mp4

5.0 MB

Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/2. Biological neural networks.mp4

5.0 MB

Reinforcement Learning Foundations/4 - Temporal Difference Methods/1. The setting.mp4

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Deep Learning Getting Started/1 - Introduction to Deep Learning/6. Training an ANN.mp4

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Deep Learning Getting Started/5 - Deep Learning Example 2/3. Building a spam model.mp4

5.2 MB

Machine Learning Foundations Linear Algebra/0 - Introduction/2. What you should know.mp4

5.4 MB

Hands-On PyTorch Machine Learning/2 - PyTorch Basics/4. Understand PyTorch autograd.mp4

5.4 MB

Deep Learning Getting Started/1 - Introduction to Deep Learning/2. Linear regression.mp4

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Deep Learning Getting Started/2 - Neural Network Architecture/3. Weights and biases.mp4

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Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/3. Transfer and activation functions.mp4

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Deep Learning Getting Started/3 - Training a Neural Network/1. Setup and initialization.mp4

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Deep Learning Getting Started/1 - Introduction to Deep Learning/5. Artificial neural networks.mp4

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Deep Learning Getting Started/6 - Deep Learning Exercise/1. Exercise problem statement.mp4

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Deep Learning Getting Started/2 - Neural Network Architecture/1. The input layer.mp4

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Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/2. Hyperparameters and neural networks.mp4

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Deep Learning Getting Started/0 - Introduction/3. Setting up the environment.mp4

6.0 MB

Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/6. Solution Manually tune hyperparameters.mp4

6.1 MB

Building Computer Vision Applications with Python/5 - Image Scaling/6. Solution Resize a picture.mp4

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Building Computer Vision Applications with Python/2 - The Basics of Image Processing/5. Rotations and flips.mp4

6.1 MB

Reinforcement Learning Foundations/6 - Conclusion/1. Your reinforcement learning journey.mp4

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Building Computer Vision Applications with Python/3 - From Color to Black and White/2. Weighted grayscale.mp4

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Building Computer Vision Applications with Python/4 - Filters/7. Solution Convolution filters.mp4

6.2 MB

Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/3. How do you improve model performance.mp4

6.2 MB

Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/4. Single-layer perceptron.mp4

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Building Computer Vision Applications with Python/6 - Fun with Cuts/5. Solution Stitch two pictures together.mp4

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Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/1. The Keras Sequential model.mp4

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Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/3. Orthogonal matrix.mp4

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Hands-On PyTorch Machine Learning/4 - Torchaudio/1. Torchaudio introduction.mp4

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Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/1. Multilayer perceptron.mp4

6.7 MB

Reinforcement Learning Foundations/3 - Monte Carlo Method/4. First visit and every visit MC prediction.mp4

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Hands-On PyTorch Machine Learning/Ex_Files_Hands_On_PyTorch_ML.zip

6.8 MB

Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/1. Overfitting and underfitting Two common ANN problems.mp4

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Hands-On PyTorch Machine Learning/2 - PyTorch Basics/1. Understand PyTorch tensors.mp4

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Reinforcement Learning Foundations/4 - Temporal Difference Methods/4. Expected SARSA.mp4

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Artificial Intelligence Foundations Thinking Machines/0 - Introduction/1. Welcome.mp4

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Building Computer Vision Applications with Python/7 - Morphological Modifications/3. Open and close.mp4

7.1 MB

Deep Learning Getting Started/5 - Deep Learning Example 2/2. Creating text representations.mp4

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Building Computer Vision Applications with Python/2 - The Basics of Image Processing/6. Challenge Manipulate some pictures.mp4

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Building Computer Vision Applications with Python/0 - Introduction/1. Computer vision under the hood.mp4

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Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/1. Matrices changing basis.mp4

7.4 MB

Hands-On PyTorch Machine Learning/2 - PyTorch Basics/2. Understand PyTorch basic operations.mp4

7.5 MB

Reinforcement Learning Foundations/3 - Monte Carlo Method/2. Exploration and exploitation.mp4

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Hands-On PyTorch Machine Learning/1 - Preparation/1. PyTorch overview.mp4

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Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/3. Transformer architecture.mp4

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Hands-On PyTorch Machine Learning/5 - Torchtext/1. Torchtext introduction.mp4

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Building Computer Vision Applications with Python/7 - Morphological Modifications/5. Solution Help a robot.mp4

7.9 MB

Building Computer Vision Applications with Python/2 - The Basics of Image Processing/2. Color encoding.mp4

7.9 MB

Deep Learning Getting Started/4 - Deep Learning Example 1/3. Creating a deep learning model.mp4

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Hands-On PyTorch Machine Learning/2 - PyTorch Basics/3. Understand PyTorch NumPy Bridge.mp4

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Building Computer Vision Applications with Python/4 - Filters/4. Gaussian filters.mp4

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Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/1. Matrices introduction.mp4

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Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/3. Inverse and determinant.mp4

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Building Computer Vision Applications with Python/4 - Filters/1. Convolution filters.mp4

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Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/4. A basic RL solution.mp4

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Machine Learning Foundations Linear Algebra/0 - Introduction/1. Introduction.mp4

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Building Computer Vision Applications with Python/2 - The Basics of Image Processing/4. Resolution.mp4

8.8 MB

Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/1. Machine learning and neural networks.mp4

8.8 MB

Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/3. Types of matrix transformation.mp4

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Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/4. How neural networks learn.mp4

8.9 MB

Building Computer Vision Applications with Python/7 - Morphological Modifications/4. Challenge Help a robot.mp4

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Reinforcement Learning Foundations/4 - Temporal Difference Methods/3. SARSAMAX (Q-learning).mp4

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Deep Learning Getting Started/4 - Deep Learning Example 1/2. Input preprocessing.mp4

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Deep Learning Getting Started/4 - Deep Learning Example 1/4. Training and evaluation.mp4

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Building Computer Vision Applications with Python/2 - The Basics of Image Processing/7. Solution Manipulate some pictures.mp4

9.5 MB

Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/2. Types of matrices.mp4

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Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/2. Gaussian elimination and finding the inverse matrix.mp4

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Machine Learning Foundations Linear Algebra/2 - Vectors Basics/3. Coordinate system.mp4

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Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/2. Use case and determine evaluation metric.mp4

9.9 MB

Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/1. Terms in reinforcement learning.mp4

10 MB

Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/5. Train the neural network using Keras.mp4

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Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/1. Introduction to eigenvalues and eigenvectors.mp4

10 MB

Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/2. The history of AI.mp4

10 MB

Building Computer Vision Applications with Python/3 - From Color to Black and White/3. Converting grayscale to black and white.mp4

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Building Computer Vision Applications with Python/1 - Setting Up Your Environment/2. Testing your environment.mp4

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Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/7. Solution Build a neural network.mp4

11 MB

Building Computer Vision Applications with Python/3 - From Color to Black and White/1. Average grayscale.mp4

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Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/4. Gram–Schmidt process.mp4

11 MB

Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/1. Defining linear algebra.mp4

11 MB

Building Computer Vision Applications with Python/4 - Filters/2. Average filters.mp4

11 MB

Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/2. Data vs. reasoning.mp4

11 MB

Building Computer Vision Applications with Python/5 - Image Scaling/2. Downscaling example.mp4

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Building Computer Vision Applications with Python/7 - Morphological Modifications/2. Erosion and dilation.mp4

11 MB

Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/3. Self-supervised learning.mp4

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Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/2. Calculating eigenvalues and eigenvectors.mp4

12 MB

Building Computer Vision Applications with Python/5 - Image Scaling/4. Upscaling example.mp4

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Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/1. Generative AI.mp4

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Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/3. The Internet of Things.mp4

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Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/4. Composition or combination of matrix transformations.mp4

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Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/4. Regularization techniques to improve overfitting models.mp4

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Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/1. Define general intelligence.mp4

12 MB

Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/4. Basis, linear independence, and span.mp4

12 MB

Building Computer Vision Applications with Python/2 - The Basics of Image Processing/1. Image representation.mp4

12 MB

Hands-On PyTorch Machine Learning/1 - Preparation/4. PyTorch data exploration.mp4

12 MB

Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/1. Monte Carlo method.mp4

12 MB

Artificial Intelligence Foundations Thinking Machines/7 - Avoiding Pitfalls/1. Pitfalls.mp4

12 MB

Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/1. Dot product of vectors.mp4

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Machine Learning Foundations Linear Algebra/2 - Vectors Basics/2. Vector arithmetic.mp4

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Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/4. Google PageRank algorithm.mp4

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Building Computer Vision Applications with Python/6 - Fun with Cuts/3. Cuts in panoramic photography.mp4

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Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/2. Foundation models.mp4

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Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/1. Big data.mp4

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Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/2. Recurrent neural networks (RNN).mp4

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Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/4. Backpropagation.mp4

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Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/3. Strong vs. weak AI.mp4

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Hands-On PyTorch Machine Learning/1 - Preparation/2. PyTorch environment setup.mp4

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Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/2. Data science.mp4

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Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/2. Artificial neural networks.mp4

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Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/3. Changing to the eigenbasis.mp4

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Hands-On PyTorch Machine Learning/4 - Torchaudio/2. Torchaudio for audio understanding.mp4

13 MB

Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/5. Regression.mp4

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Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/3. Unsupervised learning.mp4

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Hands-On PyTorch Machine Learning/3 - Torchvision/1. Torchvision introduction.mp4

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Building Computer Vision Applications with Python/6 - Fun with Cuts/1. Image cuts.mp4

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Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/2. Scalar and vector projection.mp4

14 MB

Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/1. Machine learning.mp4

14 MB

Building Computer Vision Applications with Python/7 - Morphological Modifications/1. Why modify objects.mp4

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Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/4. Plan AI.mp4

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Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/3. Perceptrons.mp4

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Building Computer Vision Applications with Python/4 - Filters/5. Edge detection filters.mp4

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Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/1. Robotics.mp4

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Hands-On PyTorch Machine Learning/5 - Torchtext/2. Torchtext for translation.mp4

14 MB

Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/2. Transforming to the new basis.mp4

14 MB

Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/2. Natural language processing.mp4

14 MB

Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/2. A basic RL problem.mp4

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Reinforcement Learning Foundations/4 - Temporal Difference Methods/2. SARSA.mp4

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Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/1. Convolutional neural networks (CNN).mp4

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Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/1. Match patterns.mp4

16 MB

Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/1. Solving linear equations using Gaussian elimination.mp4

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Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/3. Changing basis of vectors.mp4

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Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/3. Markov decision process.mp4

17 MB

Building Computer Vision Applications with Python/2 - The Basics of Image Processing/3. Image file management.mp4

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Building Computer Vision Applications with Python/3 - From Color to Black and White/4. Adaptive thresholding.mp4

21 MB

Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/2. Applications of linear algebra in ML.mp4

23 MB

Building Computer Vision Applications with Python/4 - Filters/3. Median filters.mp4

25 MB

Machine Learning Foundations Linear Algebra/2 - Vectors Basics/1. Introduction to vectors.mp4

30 MB

Building Computer Vision Applications with Python/6 - Fun with Cuts/2. Stitching two images together.mp4

44 MB

Building Computer Vision Applications with Python/Ex_Files_Computer_Vision_Deep_Dive_in_Python.zip

146 MB