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
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
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
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
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
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
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 4.4 kB
Deep Learning Getting Started/4 - Deep Learning Example 1/4. Training and evaluation.srt 4.4 kB
Deep Learning Getting Started/1 - Introduction to Deep Learning/5. Artificial neural networks.srt 4.4 kB
Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/4. Composition or combination of matrix transformations.srt 4.4 kB
Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/2. Types of matrices.srt 4.4 kB
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 4.3 kB