| - | 001. Chapter 1. What is deep learning.mp4 | 28671115 | | 520.405624 | 440 | 305 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:48:39 |
| - | 002. Chapter 1. Learning representations from data.mp4 | 33021943 | | 580.522109 | 455 | 319 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:48:43 |
| - | 003. Chapter 1. Understanding how deep learning works, in three figures.mp4 | 12616746 | | 313.887347 | 321 | 186 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:48:46 |
| - | 004. Chapter 1. Donβt believe the short-term hype.mp4 | 29266560 | | 424.507211 | 551 | 416 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:48:49 |
| - | 005. Chapter 1. Before deep learning a brief history of machine learning.mp4 | 27331028 | | 529.484626 | 412 | 277 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:48:52 |
| - | 006. Chapter 1. Decision trees, random forests, and gradient boosting machines.mp4 | 38033719 | | 656.590658 | 463 | 328 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:48:57 |
| - | 007. Chapter 1. Why deep learning Why now.mp4 | 27309627 | | 537.82059 | 406 | 270 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:01 |
| - | 008. Chapter 1. A new wave of investment.mp4 | 23667219 | | 404.72381 | 467 | 332 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:04 |
| - | 009. Chapter 2. Before we begin the mathematical building blocks of neural networks.mp4 | 21734862 | | 532.085261 | 326 | 191 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:07 |
| - | 010. Chapter 2. Data representations for neural networks.mp4 | 12836811 | | 539.585329 | 190 | 55 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:09 |
| - | 011. Chapter 2. Real-world examples of data tensors.mp4 | 19105922 | | 445.010454 | 343 | 208 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:12 |
| - | 012. Chapter 2. The gears of neural networks tensor operations.mp4 | 14297923 | | 355.613605 | 321 | 186 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:14 |
| - | 013. Chapter 2. Tensor dot.mp4 | 10970626 | | 440.15746 | 199 | 64 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:16 |
| - | 014. Chapter 2. The engine of neural networks gradient-based optimization.mp4 | 22759957 | | 572.650522 | 317 | 182 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:19 |
| - | 015. Chapter 2. Stochastic gradient descent.mp4 | 21689789 | | 514.670295 | 337 | 201 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:23 |
| - | 016. Chapter 2. Looking back at our first example.mp4 | 10185630 | | 240.67483 | 338 | 203 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:25 |
| - | 017. Chapter 3. Getting started with neural networks.mp4 | 27917620 | | 604.485079 | 369 | 234 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:28 |
| - | 018. Chapter 3. Introduction to Keras.mp4 | 18183675 | | 451.279819 | 322 | 187 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:31 |
| - | 019. Chapter 3. Setting up a deep-learning workstation.mp4 | 24249353 | | 445.846349 | 435 | 299 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:34 |
| - | 020. Chapter 3. Classifying movie reviews a binary classification example.mp4 | 25076213 | | 612.078005 | 327 | 192 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:37 |
| - | 021. Chapter 3. Validating your approach.mp4 | 16218645 | | 348.717279 | 372 | 236 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:39 |
| - | 022. Chapter 3. Classifying newswires a multiclass classification example.mp4 | 29101920 | | 634.276281 | 367 | 231 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:43 |
| - | 023. Chapter 3. Predicting house prices a regression example.mp4 | 27675658 | | 621.319546 | 356 | 221 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:46 |
| - | 024. Chapter 4. Fundamentals of machine learning.mp4 | 34247491 | | 620.948027 | 441 | 306 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:50 |
| - | 025. Chapter 4. Evaluating machine-learning models.mp4 | 28021849 | | 524.074376 | 427 | 292 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:54 |
| - | 026. Chapter 4. Data preprocessing, feature engineering, and feature learning.mp4 | 25366762 | | 507.890068 | 399 | 264 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:49:57 |
| - | 027. Chapter 4. Overfitting and underfitting.mp4 | 21480115 | | 418.237823 | 410 | 275 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:50:00 |
| - | 028. Chapter 4. Adding weight regularization.mp4 | 19302677 | | 392.951293 | 392 | 257 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:50:03 |
| - | 029. Chapter 4. The universal workflow of machine learning.mp4 | 21322247 | | 409.34458 | 416 | 281 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:50:05 |
| - | 030. Chapter 4. Developing a model that does better than a baseline.mp4 | 24389564 | | 452.371156 | 431 | 296 | 125 | h264 | aac | mov | 1280x720 | 30 | mp4 | 2023-09-06 18:50:09 |