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  1. $10 ChatGPT for 1 Year & More.txt 252 bytes
  2. Artificial Intelligence Foundations Neural Networks/0 - Introduction/2. What you should know.srt 908 bytes
  3. Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/3. Other RL algorithms.srt 916 bytes
  4. Deep Learning Getting Started/7 - Conclusion/1. Extending your deep learning education.srt 1.0 KB
  5. Reinforcement Learning Foundations/description.html 1.0 KB
  6. Hands-On PyTorch Machine Learning/description.html 1.1 KB
  7. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/5. Challenge Manually tune hyperparameters.srt 1.1 KB
  8. Machine Learning Foundations Linear Algebra/description.html 1.1 KB
  9. Building Computer Vision Applications with Python/description.html 1.1 KB
  10. Machine Learning Foundations Linear Algebra/8 - Conclusion/1. Next steps.srt 1.2 KB
  11. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/6. Challenge Build a neural network.srt 1.2 KB
  12. Building Computer Vision Applications with Python/8 - Conclusion/1. Next steps.srt 1.2 KB
  13. Deep Learning Getting Started/description.html 1.2 KB
  14. Deep Learning Getting Started/6 - Deep Learning Exercise/3. Building the RCA model.srt 1.2 KB
  15. Artificial Intelligence Foundations Neural Networks/description.html 1.2 KB
  16. Artificial Intelligence Foundations Thinking Machines/description.html 1.3 KB
  17. Artificial Intelligence Foundations Neural Networks/0 - Introduction/1. Neural networks 101 Your path to AI brilliance.srt 1.3 KB
  18. Hands-On PyTorch Machine Learning/0 - Introduction/1. Explore the capabilities of PyTorch.srt 1.4 KB
  19. Building Computer Vision Applications with Python/5 - Image Scaling/5. Challenge Resize a picture.srt 1.4 KB
  20. Building Computer Vision Applications with Python/3 - From Color to Black and White/5. Challenge Removing color.srt 1.4 KB
  21. Reinforcement Learning Foundations/3 - Monte Carlo Method/5. Monte Carlo control.srt 1.4 KB
  22. Building Computer Vision Applications with Python/0 - Introduction/3. Using the exercise files.srt 1.4 KB
  23. Building Computer Vision Applications with Python/3 - From Color to Black and White/6. Solution Removing color.srt 1.5 KB
  24. Reinforcement Learning Foundations/0 - Introduction/1. Reinforcement learning in a nutshell.srt 1.5 KB
  25. Deep Learning Getting Started/6 - Deep Learning Exercise/4. Predicting root causes with deep learning.srt 1.5 KB
  26. Deep Learning Getting Started/0 - Introduction/1. Getting started with deep learning.srt 1.5 KB
  27. Deep Learning Getting Started/6 - Deep Learning Exercise/2. Preprocessing RCA data.srt 1.5 KB
  28. Machine Learning Foundations Linear Algebra/0 - Introduction/1. Introduction.srt 1.5 KB
  29. Machine Learning Foundations Linear Algebra/0 - Introduction/2. What you should know.srt 1.6 KB
  30. Building Computer Vision Applications with Python/1 - Setting Up Your Environment/1. Installing Anaconda and OpenCV.srt 1.7 KB
  31. Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/2. Multi-agent reinforcement learning.srt 1.7 KB
  32. Building Computer Vision Applications with Python/4 - Filters/7. Solution Convolution filters.srt 1.7 KB
  33. Building Computer Vision Applications with Python/6 - Fun with Cuts/4. Challenge Stitch two pictures together.srt 1.7 KB
  34. Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/3. Inverse reinforcement learning.srt 1.8 KB
  35. Artificial Intelligence Foundations Thinking Machines/8 - Conclusion/1. Next steps.srt 1.8 KB
  36. Building Computer Vision Applications with Python/5 - Image Scaling/6. Solution Resize a picture.srt 1.8 KB
  37. Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/2. Temporal difference methods.srt 1.8 KB
  38. Reinforcement Learning Foundations/4 - Temporal Difference Methods/1. The setting.srt 1.8 KB
  39. Hands-On PyTorch Machine Learning/6 - Conclusion/1. Continuing your PyTorch learning process.srt 1.9 KB
  40. Building Computer Vision Applications with Python/6 - Fun with Cuts/5. Solution Stitch two pictures together.srt 1.9 KB
  41. Hands-On PyTorch Machine Learning/3 - Torchvision/2. Torchvision for video and image understanding.srt 1.9 KB
  42. Building Computer Vision Applications with Python/3 - From Color to Black and White/2. Weighted grayscale.srt 1.9 KB
  43. Building Computer Vision Applications with Python/4 - Filters/6. Challenge Convolution filters.srt 1.9 KB
  44. Deep Learning Getting Started/4 - Deep Learning Example 1/5. Saving and loading models.srt 1.9 KB
  45. Building Computer Vision Applications with Python/7 - Morphological Modifications/5. Solution Help a robot.srt 2.0 KB
  46. Deep Learning Getting Started/5 - Deep Learning Example 2/3. Building a spam model.srt 2.0 KB
  47. Artificial Intelligence Foundations Neural Networks/0 - Introduction/3. How to use the challenge exercise files.srt 2.1 KB
  48. Building Computer Vision Applications with Python/0 - Introduction/1. Computer vision under the hood.srt 2.1 KB
  49. Reinforcement Learning Foundations/3 - Monte Carlo Method/1. The setting.srt 2.1 KB
  50. Deep Learning Getting Started/3 - Training a Neural Network/2. Forward propagation.srt 2.1 KB
  51. Building Computer Vision Applications with Python/0 - Introduction/2. What you should know.srt 2.1 KB
  52. Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/1. Deep reinforcement learning.srt 2.2 KB
  53. Deep Learning Getting Started/4 - Deep Learning Example 1/1. The Iris classification problem.srt 2.2 KB
  54. Deep Learning Getting Started/5 - Deep Learning Example 2/4. Predictions for text.srt 2.2 KB
  55. Deep Learning Getting Started/3 - Training a Neural Network/5. Gradient descent.srt 2.4 KB
  56. Deep Learning Getting Started/4 - Deep Learning Example 1/6. Predictions with deep learning models.srt 2.4 KB
  57. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/6. Solution Manually tune hyperparameters.srt 2.5 KB
  58. Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/3. Artificial neural networks.srt 2.5 KB
  59. Reinforcement Learning Foundations/4 - Temporal Difference Methods/4. Expected SARSA.srt 2.5 KB
  60. Deep Learning Getting Started/3 - Training a Neural Network/7. Validation and testing.srt 2.6 KB
  61. Deep Learning Getting Started/1 - Introduction to Deep Learning/4. The perceptron.srt 2.6 KB
  62. Artificial Intelligence Foundations Neural Networks/6 - Conclusion/1. Next steps.srt 2.6 KB
  63. Reinforcement Learning Foundations/3 - Monte Carlo Method/3. Monte Carlo prediction.srt 2.7 KB
  64. Reinforcement Learning Foundations/3 - Monte Carlo Method/4. First visit and every visit MC prediction.srt 2.7 KB
  65. Deep Learning Getting Started/1 - Introduction to Deep Learning/1. What is deep learning.srt 2.7 KB
  66. Deep Learning Getting Started/2 - Neural Network Architecture/5. The output layer.srt 2.7 KB
  67. Building Computer Vision Applications with Python/5 - Image Scaling/3. Image upscaling methods.srt 2.8 KB
  68. Building Computer Vision Applications with Python/7 - Morphological Modifications/3. Open and close.srt 2.8 KB
  69. Reinforcement Learning Foundations/6 - Conclusion/1. Your reinforcement learning journey.srt 2.8 KB
  70. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/4. Data preprocessing.srt 2.8 KB
  71. Deep Learning Getting Started/2 - Neural Network Architecture/2. Hidden layers.srt 2.8 KB
  72. Deep Learning Getting Started/5 - Deep Learning Example 2/1. Spam classification problem.srt 2.8 KB
  73. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/5. Rotations and flips.srt 2.9 KB
  74. Building Computer Vision Applications with Python/4 - Filters/4. Gaussian filters.srt 2.9 KB
  75. Deep Learning Getting Started/3 - Training a Neural Network/8. An ANN model.srt 3.0 KB
  76. Deep Learning Getting Started/5 - Deep Learning Example 2/2. Creating text representations.srt 3.0 KB
  77. Hands-On PyTorch Machine Learning/2 - PyTorch Basics/5. Advanced PyTorch autograd.srt 3.1 KB
  78. Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/3. Orthogonal matrix.srt 3.2 KB
  79. Reinforcement Learning Foundations/4 - Temporal Difference Methods/3. SARSAMAX (Q-learning).srt 3.2 KB
  80. Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/1. Matrices changing basis.srt 3.2 KB
  81. Building Computer Vision Applications with Python/5 - Image Scaling/1. Image downscaling methods.srt 3.3 KB
  82. Artificial Intelligence Foundations Thinking Machines/0 - Introduction/1. Welcome.srt 3.3 KB
  83. Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/1. Defining linear algebra.srt 3.5 KB
  84. Building Computer Vision Applications with Python/7 - Morphological Modifications/4. Challenge Help a robot.srt 3.5 KB
  85. Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/2. Biological neural networks.srt 3.5 KB
  86. Reinforcement Learning Foundations/3 - Monte Carlo Method/2. Exploration and exploitation.srt 3.5 KB
  87. Deep Learning Getting Started/2 - Neural Network Architecture/4. Activation functions.srt 3.5 KB
  88. Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/4. A basic RL solution.srt 3.5 KB
  89. Hands-On PyTorch Machine Learning/1 - Preparation/3. PyTorch use case description.srt 3.6 KB
  90. Deep Learning Getting Started/0 - Introduction/3. Setting up the environment.srt 3.6 KB
  91. Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/2. Transforming to the new basis.srt 3.6 KB
  92. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/6. Challenge Manipulate some pictures.srt 3.7 KB
  93. Deep Learning Getting Started/3 - Training a Neural Network/10. Using available open-source models.srt 3.7 KB
  94. Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/1. Terms in reinforcement learning.srt 3.7 KB
  95. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/3. Data checks and data preparation.srt 3.7 KB
  96. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/7. Solution Manipulate some pictures.srt 3.7 KB
  97. Deep Learning Getting Started/3 - Training a Neural Network/3. Measuring accuracy and error.srt 3.8 KB
  98. Hands-On PyTorch Machine Learning/2 - PyTorch Basics/2. Understand PyTorch basic operations.srt 3.8 KB
  99. Deep Learning Getting Started/6 - Deep Learning Exercise/1. Exercise problem statement.srt 3.8 KB
  100. Deep Learning Getting Started/3 - Training a Neural Network/4. Back propagation.srt 3.8 KB
  101. Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/1. Matrices introduction.srt 3.9 KB
  102. Deep Learning Getting Started/3 - Training a Neural Network/6. Batches and epochs.srt 3.9 KB
  103. Deep Learning Getting Started/3 - Training a Neural Network/9. Reusing existing network architectures.srt 3.9 KB
  104. Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/3. Inverse and determinant.srt 3.9 KB
  105. Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/4. Gram–Schmidt process.srt 4.0 KB
  106. Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/1. Introduction to eigenvalues and eigenvectors.srt 4.0 KB
  107. Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/4. Basis, linear independence, and span.srt 4.0 KB
  108. Deep Learning Getting Started/4 - Deep Learning Example 1/3. Creating a deep learning model.srt 4.0 KB
  109. Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/2. Layers Input, hidden, and output.srt 4.0 KB
  110. Deep Learning Getting Started/1 - Introduction to Deep Learning/6. Training an ANN.srt 4.0 KB
  111. Building Computer Vision Applications with Python/3 - From Color to Black and White/3. Converting grayscale to black and white.srt 4.1 KB
  112. Hands-On PyTorch Machine Learning/2 - PyTorch Basics/4. Understand PyTorch autograd.srt 4.1 KB
  113. Deep Learning Getting Started/0 - Introduction/2. Prerequisites for the course.srt 4.1 KB
  114. Deep Learning Getting Started/1 - Introduction to Deep Learning/2. Linear regression.srt 4.2 KB
  115. Reinforcement Learning Foundations/3 - Monte Carlo Method/6. Additional modifications.srt 4.2 KB
  116. Building Computer Vision Applications with Python/4 - Filters/2. Average filters.srt 4.2 KB
  117. Deep Learning Getting Started/4 - Deep Learning Example 1/2. Input preprocessing.srt 4.2 KB
  118. Machine Learning Foundations Linear Algebra/2 - Vectors Basics/3. Coordinate system.srt 4.2 KB
  119. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/2. Color encoding.srt 4.2 KB
  120. Deep Learning Getting Started/2 - Neural Network Architecture/3. Weights and biases.srt 4.2 KB
  121. Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/2. Types of matrices.srt 4.3 KB
  122. Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/4. Composition or combination of matrix transformations.srt 4.3 KB
  123. Deep Learning Getting Started/1 - Introduction to Deep Learning/5. Artificial neural networks.srt 4.3 KB
  124. Deep Learning Getting Started/4 - Deep Learning Example 1/4. Training and evaluation.srt 4.3 KB
  125. Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/3. Types of matrix transformation.srt 4.3 KB
  126. Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/2. Calculating eigenvalues and eigenvectors.srt 4.4 KB
  127. Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/2. Gaussian elimination and finding the inverse matrix.srt 4.4 KB
  128. Deep Learning Getting Started/1 - Introduction to Deep Learning/3. An analogy for deep learning.srt 4.4 KB
  129. Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/1. Dot product of vectors.srt 4.4 KB
  130. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/2. Hyperparameters and neural networks.srt 4.5 KB
  131. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/4. Resolution.srt 4.5 KB
  132. Deep Learning Getting Started/2 - Neural Network Architecture/1. The input layer.srt 4.6 KB
  133. Building Computer Vision Applications with Python/5 - Image Scaling/2. Downscaling example.srt 4.6 KB
  134. Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/1. Monte Carlo method.srt 4.7 KB
  135. Building Computer Vision Applications with Python/6 - Fun with Cuts/3. Cuts in panoramic photography.srt 4.8 KB
  136. Hands-On PyTorch Machine Learning/4 - Torchaudio/1. Torchaudio introduction.srt 4.8 KB
  137. Deep Learning Getting Started/3 - Training a Neural Network/1. Setup and initialization.srt 4.8 KB
  138. Hands-On PyTorch Machine Learning/2 - PyTorch Basics/3. Understand PyTorch NumPy Bridge.srt 4.8 KB
  139. Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/2. Scalar and vector projection.srt 4.9 KB
  140. Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/3. Transfer and activation functions.srt 5.0 KB
  141. Building Computer Vision Applications with Python/5 - Image Scaling/4. Upscaling example.srt 5.0 KB
  142. Hands-On PyTorch Machine Learning/2 - PyTorch Basics/1. Understand PyTorch tensors.srt 5.0 KB
  143. Hands-On PyTorch Machine Learning/5 - Torchtext/1. Torchtext introduction.srt 5.0 KB
  144. Building Computer Vision Applications with Python/3 - From Color to Black and White/1. Average grayscale.srt 5.0 KB
  145. Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/3. Self-supervised learning.srt 5.2 KB
  146. Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/4. Single-layer perceptron.srt 5.3 KB
  147. Building Computer Vision Applications with Python/7 - Morphological Modifications/2. Erosion and dilation.srt 5.3 KB
  148. Hands-On PyTorch Machine Learning/4 - Torchaudio/2. Torchaudio for audio understanding.srt 5.4 KB
  149. Hands-On PyTorch Machine Learning/1 - Preparation/4. PyTorch data exploration.srt 5.5 KB
  150. Hands-On PyTorch Machine Learning/1 - Preparation/2. PyTorch environment setup.srt 5.5 KB
  151. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/7. Solution Build a neural network.srt 5.5 KB
  152. Hands-On PyTorch Machine Learning/5 - Torchtext/2. Torchtext for translation.srt 5.5 KB
  153. Building Computer Vision Applications with Python/1 - Setting Up Your Environment/2. Testing your environment.srt 5.5 KB
  154. Machine Learning Foundations Linear Algebra/2 - Vectors Basics/2. Vector arithmetic.srt 5.5 KB
  155. Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/2. Foundation models.srt 5.5 KB
  156. Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/3. Transformer architecture.srt 5.6 KB
  157. Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/3. Changing to the eigenbasis.srt 5.7 KB
  158. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/3. How do you improve model performance.srt 5.7 KB
  159. Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/1. Generative AI.srt 5.8 KB
  160. Hands-On PyTorch Machine Learning/1 - Preparation/1. PyTorch overview.srt 5.8 KB
  161. Building Computer Vision Applications with Python/6 - Fun with Cuts/1. Image cuts.srt 5.8 KB
  162. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/1. Image representation.srt 5.8 KB
  163. Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/1. Multilayer perceptron.srt 5.8 KB
  164. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/1. The Keras Sequential model.srt 5.9 KB
  165. Building Computer Vision Applications with Python/4 - Filters/5. Edge detection filters.srt 6.0 KB
  166. Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/4. Google PageRank algorithm.srt 6.0 KB
  167. Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/1. Machine learning and neural networks.srt 6.0 KB
  168. Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/1. Solving linear equations using Gaussian elimination.srt 6.1 KB
  169. Building Computer Vision Applications with Python/4 - Filters/1. Convolution filters.srt 6.3 KB
  170. Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/3. Changing basis of vectors.srt 6.4 KB
  171. Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/2. A basic RL problem.srt 6.7 KB
  172. Reinforcement Learning Foundations/4 - Temporal Difference Methods/2. SARSA.srt 6.8 KB
  173. Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/4. How neural networks learn.srt 6.8 KB
  174. Machine Learning Foundations Linear Algebra/2 - Vectors Basics/1. Introduction to vectors.srt 6.9 KB
  175. Building Computer Vision Applications with Python/4 - Filters/3. Median filters.srt 6.9 KB
  176. Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/3. The Internet of Things.srt 6.9 KB
  177. Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/3. Markov decision process.srt 7.0 KB
  178. Building Computer Vision Applications with Python/3 - From Color to Black and White/4. Adaptive thresholding.srt 7.2 KB
  179. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/2. Use case and determine evaluation metric.srt 7.2 KB
  180. 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
  181. Building Computer Vision Applications with Python/7 - Morphological Modifications/1. Why modify objects.srt 7.4 KB
  182. Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/4. Backpropagation.srt 7.6 KB
  183. Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/1. Big data.srt 7.6 KB
  184. Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/2. Applications of linear algebra in ML.srt 7.6 KB
  185. Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/2. Artificial neural networks.srt 7.9 KB
  186. Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/2. The history of AI.srt 7.9 KB
  187. Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/2. Data science.srt 8.0 KB
  188. Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/2. Data vs. reasoning.srt 8.1 KB
  189. Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/1. Robotics.srt 8.1 KB
  190. Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/3. Unsupervised learning.srt 8.1 KB
  191. Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/1. Match patterns.srt 8.1 KB
  192. Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/2. Natural language processing.srt 8.2 KB
  193. Artificial Intelligence Foundations Thinking Machines/7 - Avoiding Pitfalls/1. Pitfalls.srt 8.2 KB
  194. Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/3. Strong vs. weak AI.srt 8.3 KB
  195. Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/1. Machine learning.srt 8.3 KB
  196. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/5. Train the neural network using Keras.srt 8.4 KB
  197. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/3. Image file management.srt 8.4 KB
  198. Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/4. Plan AI.srt 8.4 KB
  199. Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/1. Define general intelligence.srt 8.4 KB
  200. Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/3. Perceptrons.srt 8.5 KB
  201. Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/5. Regression.srt 8.9 KB
  202. Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/2. Recurrent neural networks (RNN).srt 9.8 KB
  203. Building Computer Vision Applications with Python/6 - Fun with Cuts/2. Stitching two images together.srt 9.9 KB
  204. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/4. Regularization techniques to improve overfitting models.srt 11.3 KB
  205. Hands-On PyTorch Machine Learning/3 - Torchvision/1. Torchvision introduction.srt 12.0 KB
  206. Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/1. Convolutional neural networks (CNN).srt 12.2 KB
  207. Machine Learning Foundations Linear Algebra/Ex_Files_ML_Foundations_Linear_Algebra.zip 33.3 KB
  208. Deep Learning Getting Started/Ex_Files_Deep_Learning_Getting_Started.zip 103.0 KB
  209. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/5. Challenge Manually tune hyperparameters.mp4 1.1 MB
  210. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/6. Challenge Build a neural network.mp4 1.3 MB
  211. Reinforcement Learning Foundations/3 - Monte Carlo Method/5. Monte Carlo control.mp4 1.4 MB
  212. Deep Learning Getting Started/7 - Conclusion/1. Extending your deep learning education.mp4 1.5 MB
  213. Artificial Intelligence Foundations Neural Networks/0 - Introduction/2. What you should know.mp4 1.6 MB
  214. Hands-On PyTorch Machine Learning/6 - Conclusion/1. Continuing your PyTorch learning process.mp4 1.7 MB
  215. Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/2. Multi-agent reinforcement learning.mp4 1.8 MB
  216. Building Computer Vision Applications with Python/0 - Introduction/3. Using the exercise files.mp4 1.8 MB
  217. Building Computer Vision Applications with Python/8 - Conclusion/1. Next steps.mp4 1.8 MB
  218. Building Computer Vision Applications with Python/1 - Setting Up Your Environment/1. Installing Anaconda and OpenCV.mp4 1.9 MB
  219. Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/3. Inverse reinforcement learning.mp4 2.2 MB
  220. Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/2. Temporal difference methods.mp4 2.3 MB
  221. Reinforcement Learning Foundations/3 - Monte Carlo Method/3. Monte Carlo prediction.mp4 2.4 MB
  222. Machine Learning Foundations Linear Algebra/8 - Conclusion/1. Next steps.mp4 2.5 MB
  223. Hands-On PyTorch Machine Learning/0 - Introduction/1. Explore the capabilities of PyTorch.mp4 2.5 MB
  224. Deep Learning Getting Started/1 - Introduction to Deep Learning/4. The perceptron.mp4 2.6 MB
  225. Artificial Intelligence Foundations Neural Networks/6 - Conclusion/1. Next steps.mp4 2.6 MB
  226. Deep Learning Getting Started/1 - Introduction to Deep Learning/1. What is deep learning.mp4 2.6 MB
  227. Deep Learning Getting Started/6 - Deep Learning Exercise/4. Predicting root causes with deep learning.mp4 2.7 MB
  228. Building Computer Vision Applications with Python/0 - Introduction/2. What you should know.mp4 2.7 MB
  229. Deep Learning Getting Started/3 - Training a Neural Network/2. Forward propagation.mp4 2.8 MB
  230. Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/3. Artificial neural networks.mp4 2.9 MB
  231. Building Computer Vision Applications with Python/3 - From Color to Black and White/5. Challenge Removing color.mp4 2.9 MB
  232. Building Computer Vision Applications with Python/5 - Image Scaling/5. Challenge Resize a picture.mp4 2.9 MB
  233. Deep Learning Getting Started/3 - Training a Neural Network/5. Gradient descent.mp4 3.0 MB
  234. Deep Learning Getting Started/4 - Deep Learning Example 1/5. Saving and loading models.mp4 3.0 MB
  235. Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/3. Other RL algorithms.mp4 3.2 MB
  236. Deep Learning Getting Started/3 - Training a Neural Network/7. Validation and testing.mp4 3.2 MB
  237. Reinforcement Learning Foundations/3 - Monte Carlo Method/1. The setting.mp4 3.2 MB
  238. Deep Learning Getting Started/2 - Neural Network Architecture/5. The output layer.mp4 3.4 MB
  239. Building Computer Vision Applications with Python/5 - Image Scaling/3. Image upscaling methods.mp4 3.5 MB
  240. Deep Learning Getting Started/3 - Training a Neural Network/8. An ANN model.mp4 3.5 MB
  241. Hands-On PyTorch Machine Learning/1 - Preparation/3. PyTorch use case description.mp4 3.6 MB
  242. Building Computer Vision Applications with Python/6 - Fun with Cuts/4. Challenge Stitch two pictures together.mp4 3.6 MB
  243. Deep Learning Getting Started/6 - Deep Learning Exercise/3. Building the RCA model.mp4 3.6 MB
  244. Reinforcement Learning Foundations/0 - Introduction/1. Reinforcement learning in a nutshell.mp4 3.7 MB
  245. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/4. Data preprocessing.mp4 3.7 MB
  246. Deep Learning Getting Started/5 - Deep Learning Example 2/1. Spam classification problem.mp4 3.7 MB
  247. Artificial Intelligence Foundations Neural Networks/0 - Introduction/3. How to use the challenge exercise files.mp4 3.7 MB
  248. Deep Learning Getting Started/2 - Neural Network Architecture/4. Activation functions.mp4 3.9 MB
  249. Deep Learning Getting Started/0 - Introduction/1. Getting started with deep learning.mp4 4.0 MB
  250. Deep Learning Getting Started/6 - Deep Learning Exercise/2. Preprocessing RCA data.mp4 4.0 MB
  251. Deep Learning Getting Started/5 - Deep Learning Example 2/4. Predictions for text.mp4 4.1 MB
  252. Building Computer Vision Applications with Python/3 - From Color to Black and White/6. Solution Removing color.mp4 4.2 MB
  253. Building Computer Vision Applications with Python/5 - Image Scaling/1. Image downscaling methods.mp4 4.2 MB
  254. Deep Learning Getting Started/3 - Training a Neural Network/9. Reusing existing network architectures.mp4 4.2 MB
  255. Artificial Intelligence Foundations Thinking Machines/8 - Conclusion/1. Next steps.mp4 4.3 MB
  256. Reinforcement Learning Foundations/5 - Modified Forms of Reinforcement/1. Deep reinforcement learning.mp4 4.3 MB
  257. Deep Learning Getting Started/3 - Training a Neural Network/10. Using available open-source models.mp4 4.3 MB
  258. Artificial Intelligence Foundations Neural Networks/0 - Introduction/1. Neural networks 101 Your path to AI brilliance.mp4 4.4 MB
  259. Hands-On PyTorch Machine Learning/3 - Torchvision/2. Torchvision for video and image understanding.mp4 4.5 MB
  260. Deep Learning Getting Started/1 - Introduction to Deep Learning/3. An analogy for deep learning.mp4 4.5 MB
  261. Reinforcement Learning Foundations/3 - Monte Carlo Method/6. Additional modifications.mp4 4.5 MB
  262. Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/2. Layers Input, hidden, and output.mp4 4.5 MB
  263. Deep Learning Getting Started/4 - Deep Learning Example 1/6. Predictions with deep learning models.mp4 4.6 MB
  264. Deep Learning Getting Started/2 - Neural Network Architecture/2. Hidden layers.mp4 4.6 MB
  265. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/3. Data checks and data preparation.mp4 4.7 MB
  266. Deep Learning Getting Started/4 - Deep Learning Example 1/1. The Iris classification problem.mp4 4.7 MB
  267. Deep Learning Getting Started/3 - Training a Neural Network/3. Measuring accuracy and error.mp4 4.7 MB
  268. Building Computer Vision Applications with Python/4 - Filters/6. Challenge Convolution filters.mp4 4.8 MB
  269. Deep Learning Getting Started/3 - Training a Neural Network/4. Back propagation.mp4 4.8 MB
  270. Deep Learning Getting Started/3 - Training a Neural Network/6. Batches and epochs.mp4 4.8 MB
  271. Deep Learning Getting Started/0 - Introduction/2. Prerequisites for the course.mp4 4.9 MB
  272. Hands-On PyTorch Machine Learning/2 - PyTorch Basics/5. Advanced PyTorch autograd.mp4 5.0 MB
  273. Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/2. Biological neural networks.mp4 5.0 MB
  274. Reinforcement Learning Foundations/4 - Temporal Difference Methods/1. The setting.mp4 5.2 MB
  275. Deep Learning Getting Started/1 - Introduction to Deep Learning/6. Training an ANN.mp4 5.2 MB
  276. Deep Learning Getting Started/5 - Deep Learning Example 2/3. Building a spam model.mp4 5.2 MB
  277. Machine Learning Foundations Linear Algebra/0 - Introduction/2. What you should know.mp4 5.4 MB
  278. Hands-On PyTorch Machine Learning/2 - PyTorch Basics/4. Understand PyTorch autograd.mp4 5.4 MB
  279. Deep Learning Getting Started/1 - Introduction to Deep Learning/2. Linear regression.mp4 5.6 MB
  280. Deep Learning Getting Started/2 - Neural Network Architecture/3. Weights and biases.mp4 5.6 MB
  281. Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/3. Transfer and activation functions.mp4 5.7 MB
  282. Deep Learning Getting Started/3 - Training a Neural Network/1. Setup and initialization.mp4 5.7 MB
  283. Deep Learning Getting Started/1 - Introduction to Deep Learning/5. Artificial neural networks.mp4 5.8 MB
  284. Deep Learning Getting Started/6 - Deep Learning Exercise/1. Exercise problem statement.mp4 5.8 MB
  285. Deep Learning Getting Started/2 - Neural Network Architecture/1. The input layer.mp4 5.9 MB
  286. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/2. Hyperparameters and neural networks.mp4 6.0 MB
  287. Deep Learning Getting Started/0 - Introduction/3. Setting up the environment.mp4 6.0 MB
  288. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/6. Solution Manually tune hyperparameters.mp4 6.1 MB
  289. Building Computer Vision Applications with Python/5 - Image Scaling/6. Solution Resize a picture.mp4 6.1 MB
  290. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/5. Rotations and flips.mp4 6.1 MB
  291. Reinforcement Learning Foundations/6 - Conclusion/1. Your reinforcement learning journey.mp4 6.2 MB
  292. Building Computer Vision Applications with Python/3 - From Color to Black and White/2. Weighted grayscale.mp4 6.2 MB
  293. Building Computer Vision Applications with Python/4 - Filters/7. Solution Convolution filters.mp4 6.2 MB
  294. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/3. How do you improve model performance.mp4 6.2 MB
  295. Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/4. Single-layer perceptron.mp4 6.4 MB
  296. Building Computer Vision Applications with Python/6 - Fun with Cuts/5. Solution Stitch two pictures together.mp4 6.4 MB
  297. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/1. The Keras Sequential model.mp4 6.5 MB
  298. Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/3. Orthogonal matrix.mp4 6.6 MB
  299. Hands-On PyTorch Machine Learning/4 - Torchaudio/1. Torchaudio introduction.mp4 6.6 MB
  300. Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/1. Multilayer perceptron.mp4 6.7 MB
  301. Reinforcement Learning Foundations/3 - Monte Carlo Method/4. First visit and every visit MC prediction.mp4 6.8 MB
  302. Hands-On PyTorch Machine Learning/Ex_Files_Hands_On_PyTorch_ML.zip 6.8 MB
  303. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/1. Overfitting and underfitting Two common ANN problems.mp4 6.9 MB
  304. Hands-On PyTorch Machine Learning/2 - PyTorch Basics/1. Understand PyTorch tensors.mp4 7.0 MB
  305. Reinforcement Learning Foundations/4 - Temporal Difference Methods/4. Expected SARSA.mp4 7.1 MB
  306. Artificial Intelligence Foundations Thinking Machines/0 - Introduction/1. Welcome.mp4 7.1 MB
  307. Building Computer Vision Applications with Python/7 - Morphological Modifications/3. Open and close.mp4 7.1 MB
  308. Deep Learning Getting Started/5 - Deep Learning Example 2/2. Creating text representations.mp4 7.1 MB
  309. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/6. Challenge Manipulate some pictures.mp4 7.2 MB
  310. Building Computer Vision Applications with Python/0 - Introduction/1. Computer vision under the hood.mp4 7.4 MB
  311. Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/1. Matrices changing basis.mp4 7.4 MB
  312. Hands-On PyTorch Machine Learning/2 - PyTorch Basics/2. Understand PyTorch basic operations.mp4 7.5 MB
  313. Reinforcement Learning Foundations/3 - Monte Carlo Method/2. Exploration and exploitation.mp4 7.7 MB
  314. Hands-On PyTorch Machine Learning/1 - Preparation/1. PyTorch overview.mp4 7.7 MB
  315. Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/3. Transformer architecture.mp4 7.8 MB
  316. Hands-On PyTorch Machine Learning/5 - Torchtext/1. Torchtext introduction.mp4 7.9 MB
  317. Building Computer Vision Applications with Python/7 - Morphological Modifications/5. Solution Help a robot.mp4 7.9 MB
  318. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/2. Color encoding.mp4 7.9 MB
  319. Deep Learning Getting Started/4 - Deep Learning Example 1/3. Creating a deep learning model.mp4 8.1 MB
  320. Hands-On PyTorch Machine Learning/2 - PyTorch Basics/3. Understand PyTorch NumPy Bridge.mp4 8.1 MB
  321. Building Computer Vision Applications with Python/4 - Filters/4. Gaussian filters.mp4 8.2 MB
  322. Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/1. Matrices introduction.mp4 8.4 MB
  323. Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/3. Inverse and determinant.mp4 8.4 MB
  324. Building Computer Vision Applications with Python/4 - Filters/1. Convolution filters.mp4 8.5 MB
  325. Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/4. A basic RL solution.mp4 8.6 MB
  326. Machine Learning Foundations Linear Algebra/0 - Introduction/1. Introduction.mp4 8.6 MB
  327. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/4. Resolution.mp4 8.8 MB
  328. Artificial Intelligence Foundations Neural Networks/1 - What Are Neural Networks/1. Machine learning and neural networks.mp4 8.8 MB
  329. Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/3. Types of matrix transformation.mp4 8.9 MB
  330. Artificial Intelligence Foundations Neural Networks/2 - Key Components in Neural Network Architecture/4. How neural networks learn.mp4 8.9 MB
  331. Building Computer Vision Applications with Python/7 - Morphological Modifications/4. Challenge Help a robot.mp4 9.0 MB
  332. Reinforcement Learning Foundations/4 - Temporal Difference Methods/3. SARSAMAX (Q-learning).mp4 9.1 MB
  333. Deep Learning Getting Started/4 - Deep Learning Example 1/2. Input preprocessing.mp4 9.4 MB
  334. Deep Learning Getting Started/4 - Deep Learning Example 1/4. Training and evaluation.mp4 9.4 MB
  335. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/7. Solution Manipulate some pictures.mp4 9.5 MB
  336. Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/2. Types of matrices.mp4 9.6 MB
  337. Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/2. Gaussian elimination and finding the inverse matrix.mp4 9.7 MB
  338. Machine Learning Foundations Linear Algebra/2 - Vectors Basics/3. Coordinate system.mp4 9.8 MB
  339. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/2. Use case and determine evaluation metric.mp4 9.9 MB
  340. Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/1. Terms in reinforcement learning.mp4 10.2 MB
  341. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/5. Train the neural network using Keras.mp4 10.3 MB
  342. Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/1. Introduction to eigenvalues and eigenvectors.mp4 10.4 MB
  343. Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/2. The history of AI.mp4 10.4 MB
  344. Building Computer Vision Applications with Python/3 - From Color to Black and White/3. Converting grayscale to black and white.mp4 10.5 MB
  345. Building Computer Vision Applications with Python/1 - Setting Up Your Environment/2. Testing your environment.mp4 10.6 MB
  346. Artificial Intelligence Foundations Neural Networks/4 - Build a Simple Neural Network Using Keras/7. Solution Build a neural network.mp4 10.8 MB
  347. Building Computer Vision Applications with Python/3 - From Color to Black and White/1. Average grayscale.mp4 10.9 MB
  348. Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/4. Gram–Schmidt process.mp4 11.1 MB
  349. Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/1. Defining linear algebra.mp4 11.2 MB
  350. Building Computer Vision Applications with Python/4 - Filters/2. Average filters.mp4 11.4 MB
  351. Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/2. Data vs. reasoning.mp4 11.4 MB
  352. Building Computer Vision Applications with Python/5 - Image Scaling/2. Downscaling example.mp4 11.4 MB
  353. Building Computer Vision Applications with Python/7 - Morphological Modifications/2. Erosion and dilation.mp4 11.4 MB
  354. Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/3. Self-supervised learning.mp4 11.4 MB
  355. Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/2. Calculating eigenvalues and eigenvectors.mp4 11.5 MB
  356. Building Computer Vision Applications with Python/5 - Image Scaling/4. Upscaling example.mp4 11.7 MB
  357. Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/1. Generative AI.mp4 11.7 MB
  358. Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/3. The Internet of Things.mp4 11.7 MB
  359. Machine Learning Foundations Linear Algebra/4 - Introduction to Matrices/4. Composition or combination of matrix transformations.mp4 11.8 MB
  360. Artificial Intelligence Foundations Neural Networks/5 - Best Practices for Optimizing a Neural Network/4. Regularization techniques to improve overfitting models.mp4 11.8 MB
  361. Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/1. Define general intelligence.mp4 11.9 MB
  362. Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/4. Basis, linear independence, and span.mp4 12.0 MB
  363. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/1. Image representation.mp4 12.1 MB
  364. Hands-On PyTorch Machine Learning/1 - Preparation/4. PyTorch data exploration.mp4 12.1 MB
  365. Reinforcement Learning Foundations/2 - Reinforcement Learning Algorithms/1. Monte Carlo method.mp4 12.2 MB
  366. Artificial Intelligence Foundations Thinking Machines/7 - Avoiding Pitfalls/1. Pitfalls.mp4 12.3 MB
  367. Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/1. Dot product of vectors.mp4 12.4 MB
  368. Machine Learning Foundations Linear Algebra/2 - Vectors Basics/2. Vector arithmetic.mp4 12.4 MB
  369. Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/4. Google PageRank algorithm.mp4 12.4 MB
  370. Building Computer Vision Applications with Python/6 - Fun with Cuts/3. Cuts in panoramic photography.mp4 12.5 MB
  371. Artificial Intelligence Foundations Thinking Machines/6 - What Has Changed/2. Foundation models.mp4 12.6 MB
  372. Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/1. Big data.mp4 12.7 MB
  373. Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/2. Recurrent neural networks (RNN).mp4 12.8 MB
  374. Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/4. Backpropagation.mp4 13.0 MB
  375. Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/3. Strong vs. weak AI.mp4 13.0 MB
  376. Hands-On PyTorch Machine Learning/1 - Preparation/2. PyTorch environment setup.mp4 13.0 MB
  377. Artificial Intelligence Foundations Thinking Machines/5 - Mixing with Other Technologies/2. Data science.mp4 13.1 MB
  378. Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/2. Artificial neural networks.mp4 13.1 MB
  379. Machine Learning Foundations Linear Algebra/7 - Eigenvalues and Eigenvectors/3. Changing to the eigenbasis.mp4 13.2 MB
  380. Hands-On PyTorch Machine Learning/4 - Torchaudio/2. Torchaudio for audio understanding.mp4 13.2 MB
  381. Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/5. Regression.mp4 13.5 MB
  382. Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/3. Unsupervised learning.mp4 13.6 MB
  383. Hands-On PyTorch Machine Learning/3 - Torchvision/1. Torchvision introduction.mp4 13.7 MB
  384. Building Computer Vision Applications with Python/6 - Fun with Cuts/1. Image cuts.mp4 13.7 MB
  385. Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/2. Scalar and vector projection.mp4 13.8 MB
  386. Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/1. Machine learning.mp4 13.8 MB
  387. Building Computer Vision Applications with Python/7 - Morphological Modifications/1. Why modify objects.mp4 13.8 MB
  388. Artificial Intelligence Foundations Thinking Machines/1 - What Is Artificial Intelligence/4. Plan AI.mp4 13.9 MB
  389. Artificial Intelligence Foundations Thinking Machines/2 - The Rise of Machine Learning/3. Perceptrons.mp4 14.1 MB
  390. Building Computer Vision Applications with Python/4 - Filters/5. Edge detection filters.mp4 14.2 MB
  391. Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/1. Robotics.mp4 14.2 MB
  392. Hands-On PyTorch Machine Learning/5 - Torchtext/2. Torchtext for translation.mp4 14.3 MB
  393. Machine Learning Foundations Linear Algebra/6 - Matrices from Orthogonality to Gram–Schmidt Process/2. Transforming to the new basis.mp4 14.4 MB
  394. Artificial Intelligence Foundations Thinking Machines/4 - Common AI Programs/2. Natural language processing.mp4 14.5 MB
  395. Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/2. A basic RL problem.mp4 15.1 MB
  396. Reinforcement Learning Foundations/4 - Temporal Difference Methods/2. SARSA.mp4 15.2 MB
  397. Artificial Intelligence Foundations Neural Networks/3 - Other Types of Neural Networks/1. Convolutional neural networks (CNN).mp4 15.6 MB
  398. Artificial Intelligence Foundations Thinking Machines/3 - Finding the Right Approach/1. Match patterns.mp4 15.6 MB
  399. Machine Learning Foundations Linear Algebra/5 - Gaussian Elimination/1. Solving linear equations using Gaussian elimination.mp4 17.1 MB
  400. Machine Learning Foundations Linear Algebra/3 - Vector Projections and Basis/3. Changing basis of vectors.mp4 17.1 MB
  401. Reinforcement Learning Foundations/1 - Getting Started with Reinforcement Learning/3. Markov decision process.mp4 17.4 MB
  402. Building Computer Vision Applications with Python/2 - The Basics of Image Processing/3. Image file management.mp4 19.1 MB
  403. Building Computer Vision Applications with Python/3 - From Color to Black and White/4. Adaptive thresholding.mp4 20.9 MB
  404. Machine Learning Foundations Linear Algebra/1 - Introduction to Linear Algebra/2. Applications of linear algebra in ML.mp4 22.8 MB
  405. Building Computer Vision Applications with Python/4 - Filters/3. Median filters.mp4 25.4 MB
  406. Machine Learning Foundations Linear Algebra/2 - Vectors Basics/1. Introduction to vectors.mp4 29.9 MB
  407. Building Computer Vision Applications with Python/6 - Fun with Cuts/2. Stitching two images together.mp4 44.1 MB
  408. Building Computer Vision Applications with Python/Ex_Files_Computer_Vision_Deep_Dive_in_Python.zip 145.8 MB

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