Udacity - Deep Learning Foundation v1.0.0 - 磁力管家 - 男人都爱上的磁力连接搜索引擎

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种子哈希：980d687ac1263d7cbdd6cd5eaac2cb239faf8a7e
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收录时间：2018-11-26
最近下载：2025-05-15
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文档列表

Part 02-Module 03-Lesson 01_MiniFlow/07. Pixels are Features!-qE5YYXtPq9U.en-US.vtt 72 Bytes
Part 02-Module 03-Lesson 01_MiniFlow/07. Pixels are Features!-qE5YYXtPq9U.pt-BR.vtt 91 Bytes
Part 02-Module 05-Lesson 02_Convolutional Networks/01. Intro to CNNs-B61jxZ4rkMs.zh-CN.vtt 301 Bytes
Part 02-Module 05-Lesson 02_Convolutional Networks/01. Intro to CNNs-B61jxZ4rkMs.en.vtt 303 Bytes
Part 02-Module 05-Lesson 02_Convolutional Networks/01. Intro to CNNs-B61jxZ4rkMs.en-US.vtt 309 Bytes
Part 02-Module 05-Lesson 02_Convolutional Networks/01. Intro to CNNs-B61jxZ4rkMs.pt-BR.vtt 324 Bytes
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.pt-BR.vtt 364 Bytes
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.zh-CN.vtt 390 Bytes
Part 07-Module 01-Lesson 03_Training Neural Networks/10. Random Restart-idyBBCzXiqg.zh-CN.vtt 419 Bytes
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.en.vtt 420 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.pt-BR.vtt 420 Bytes
README.txt 454 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.zh-CN.vtt 456 Bytes
Part 07-Module 01-Lesson 03_Training Neural Networks/10. Random Restart-idyBBCzXiqg.en.vtt 466 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.zh-CN.vtt 468 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.pt-BR.vtt 472 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/28. Mini Project Introduction-Rgf3YVFWl-M.zh-CN.vtt 475 Bytes
Part 02-Module 05-Lesson 02_Convolutional Networks/01. Intro to CNNs-B61jxZ4rkMs.ja-JP.vtt 477 Bytes
Part 07-Module 01-Lesson 03_Training Neural Networks/10. Random Restart-idyBBCzXiqg.pt-BR.vtt 478 Bytes
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.zh-CN.vtt 481 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.pt-BR.vtt 482 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.zh-CN.vtt 487 Bytes
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.en.vtt 495 Bytes
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.pt-BR.vtt 501 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.en.vtt 505 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.en.vtt 508 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/28. Mini Project Introduction-Rgf3YVFWl-M.en.vtt 510 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.en.vtt 526 Bytes
Part 01-Module 03-Lesson 02_Intro to Neural Networks/01. Introducing Luis-nto-stLuN6M.zh-CN.vtt 535 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/28. Mini Project Introduction-Rgf3YVFWl-M.pt-BR.vtt 538 Bytes
Part 07-Module 01-Lesson 05_Keras/06. Keras Lab-a50un22BsLI.zh-CN.vtt 540 Bytes
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Part 02-Module 05-Lesson 02_Convolutional Networks/07. Feature-Map-Sizes-Question-lp1NrLZnCUM.zh-CN.vtt 555 Bytes
Part 02-Module 05-Lesson 01_Deep Neural Networks/10. Regularization-Quiz-E0eEW6V0_sA.zh-CN.vtt 557 Bytes
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Part 02-Module 05-Lesson 02_Convolutional Networks/07. Feature-Map-Sizes-Question-lp1NrLZnCUM.en.vtt 594 Bytes
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Part 02-Module 05-Lesson 02_Convolutional Networks/02. Color-Question-BdQccpMwk80.zh-CN.vtt 612 Bytes
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Part 02-Module 05-Lesson 01_Deep Neural Networks/10. Regularization-Quiz-E0eEW6V0_sA.pt-BR.vtt 643 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/20. Solution ROC Curve-sdUUf6RRmXI.pt-BR.vtt 643 Bytes
Part 07-Module 01-Lesson 06_TensorFlow/17. Conclusion-wOiUQDgGD9E.zh-CN.vtt 655 Bytes
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Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/19. 17 Quiz ROC Curve 1 PT2 V1-Xv3v59_CfEU.pt-BR.vtt 678 Bytes
Part 02-Module 05-Lesson 02_Convolutional Networks/02. Color-Question-BdQccpMwk80.pt-BR.vtt 683 Bytes
Part 07-Module 01-Lesson 04_Sentiment Analysis/01. Introducing Andrew Trask-ltO71Bm8b3M.zh-CN.vtt 685 Bytes
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/01. Introducing Alexis-38ExGpdyvJI.en.vtt 694 Bytes
Part 09-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/07. Remember Gate-0qlm86HaXuU.pt-BR.vtt 700 Bytes
Part 03-Module 04-Lesson 04_Generate TV Scripts/01. Project-3-Intro-qNpv7IjQzo0.en-US.vtt 701 Bytes
Part 02-Module 04-Lesson 02_Intro to TensorFlow/17. 17 L Transition Into Practical Aspects Of Learning-bKqkRFOOKoA.pt-BR.vtt 707 Bytes
Part 02-Module 04-Lesson 02_Intro to TensorFlow/13. 13 L One Hot Encoding-phYsxqlilUk.en.vtt 707 Bytes
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Part 07-Module 01-Lesson 01_Introduction to Neural Networks/21. Formula For Cross 1-qvr_ego_d6w.pt-BR.vtt 719 Bytes
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Part 07-Module 01-Lesson 06_TensorFlow/17. Conclusion-wOiUQDgGD9E.en.vtt 725 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/19. 17 Quiz ROC Curve 1 PT2 V1-Xv3v59_CfEU.zh-CN.vtt 729 Bytes
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Part 09-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/07. Remember Gate-0qlm86HaXuU.en.vtt 734 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/10. 10 Quiz Random Vs Preinitiliazed Weights V3-DRC1e4XGl2M.zh-CN.vtt 734 Bytes
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Part 07-Module 01-Lesson 04_Sentiment Analysis/01. Introducing Andrew Trask-ltO71Bm8b3M.en.vtt 746 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/10. 10 Quiz Random Vs Preinitiliazed Weights V3-DRC1e4XGl2M.pt-BR.vtt 754 Bytes
Part 01-Module 02-Lesson 01_Regression/01. Welcome to Week One-10M2DnJuziE.en-US.vtt 756 Bytes
Part 02-Module 04-Lesson 02_Intro to TensorFlow/18. Numerical Stability-_SbGcOS-jcQ.en-US.vtt 764 Bytes
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Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/14. Solution Sensitivty And Specificity-GBZjyeMjKxc.pt-BR.vtt 772 Bytes
Part 02-Module 04-Lesson 02_Intro to TensorFlow/21. 29 L Optimizing A Logistic Classifier-U_7nO1dm2tY.zh-CN.vtt 777 Bytes
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Part 02-Module 04-Lesson 02_Intro to TensorFlow/01. Intro to Vincent-0_M6a04ofz8.zh-CN.vtt 790 Bytes
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/19. 17 Quiz ROC Curve 1 PT2 V1-Xv3v59_CfEU.en.vtt 791 Bytes
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Part 04-Module 01-Lesson 02_Siraj's Video Generation/index.html 3.6 kB
Part 11-Module 02-Lesson 01_Teach a Quadcopter How to Fly/index.html 3.6 kB
Part 03-Module 08-Lesson 01_Siraj's Image Generation/index.html 3.6 kB
Part 08-Module 02-Lesson 01_CNN Project Dog Breed Classifier/index.html 3.6 kB
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Part 02-Module 03-Lesson 01_MiniFlow/img/dl2dw2-grad.png 3.8 kB
Part 02-Module 05-Lesson 04_Image Classification/index.html 3.8 kB
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Part 06-Module 01-Lesson 02_Applying Deep Learning/02. Style Transfer.html 12.4 kB
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Part 09-Module 01-Lesson 01_Recurrent Neural Networks/22. BPTT Quiz 3.html 12.4 kB
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Part 01-Module 01-Lesson 01_Welcome/06. Community Support.html 12.5 kB
Part 01-Module 01-Lesson 03_Jupyter Notebooks/02. What are Jupyter notebooks.html 12.6 kB
Part 06-Module 01-Lesson 04_Jupyter Notebooks/02. What are Jupyter notebooks.html 12.6 kB
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Part 06-Module 01-Lesson 01_Welcome to Deep Learning/04. Program Structure.html 13.1 kB
Part 03-Module 04-Lesson 04_Generate TV Scripts/Project Rubric - Generate TV Scripts.html 13.2 kB
assets/css/fonts/KaTeX_Size1-Regular.ttf 13.2 kB
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Part 02-Module 03-Lesson 01_MiniFlow/06. Learning and Loss.html 13.6 kB
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Part 06-Module 01-Lesson 05_Matrix Math and NumPy Refresher/03. Data in NumPy.html 13.7 kB
Part 01-Module 03-Lesson 01_Matrix Math and NumPy Refresher/03. Data in NumPy.html 13.7 kB
Part 01-Module 03-Lesson 02_Intro to Neural Networks/09. The Simplest Neural Network.html 13.7 kB
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Part 08-Module 01-Lesson 01_Cloud Computing/img/aws-create-account.png 13.8 kB
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assets/css/fonts/KaTeX_Script-Regular.woff 13.9 kB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/24. RNN Summary.html 13.9 kB
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assets/css/fonts/KaTeX_SansSerif-Regular.woff2 14.0 kB
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Part 09-Module 01-Lesson 01_Recurrent Neural Networks/19. Backpropagation Through Time (part c).html 14.4 kB
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Part 02-Module 02-Lesson 02_Intro to TFLearn/02. ReLU and Softmax Activation Functions.html 14.6 kB
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Part 02-Module 04-Lesson 02_Intro to TensorFlow/26. Epochs.html 15.1 kB
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/24. Refresh on Confusion Matrices.html 15.1 kB
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Part 09-Module 01-Lesson 01_Recurrent Neural Networks/06. The Feedforward Process.html 15.1 kB
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Part 02-Module 03-Lesson 01_MiniFlow/04. Forward Propagation.html 15.3 kB
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Part 11-Module 01-Lesson 05_Monte Carlo Methods/22. Summary.html 15.5 kB
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Part 07-Module 01-Lesson 05_Keras/02. Keras.html 15.9 kB
Part 01-Module 02-Lesson 01_Regression/04. Linear Regression.html 16.0 kB
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Part 07-Module 01-Lesson 01_Introduction to Neural Networks/24. Gradient Descent.html 16.5 kB
Part 01-Module 01-Lesson 01_Welcome/07. Deadline Policy.html 16.6 kB
Part 06-Module 01-Lesson 01_Welcome to Deep Learning/06. Deadline Policy.html 16.7 kB
assets/css/fonts/KaTeX_SansSerif-Regular.woff 16.8 kB
Part 02-Module 04-Lesson 02_Intro to TensorFlow/11. ReLU and Softmax Activation Functions.html 16.9 kB
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assets/css/fonts/KaTeX_Typewriter-Regular.woff2 17.5 kB
Part 02-Module 05-Lesson 01_Deep Neural Networks/img/two-layer-network.png 17.6 kB
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Part 11-Module 01-Lesson 05_Monte Carlo Methods/15. Exploration vs. Exploitation.html 17.8 kB
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Part 02-Module 03-Lesson 01_MiniFlow/09. Cost.html 18.2 kB
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Part 07-Module 01-Lesson 01_Introduction to Neural Networks/28. Gradient Descent Vs Perceptron Algorithm-uL5LuRPivTA.mp4 3.4 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/01. GANs Intro-F7XgI6TmaGI.mp4 3.4 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/01. GANs Intro-F7XgI6TmaGI.mp4 3.4 MB
Part 10-Module 01-Lesson 02_Deep Convolutional GANs/07. Discriminator-XRqOUbf96eI.mp4 3.4 MB
Part 04-Module 02-Lesson 03_Deep Convolutional GANs/07. Discriminator-XRqOUbf96eI.mp4 3.4 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/34. Calculating The Gradient 1 -tVuZDbUrzzI.mp4 3.5 MB
Part 02-Module 01-Lesson 01_Model Evaluation and Validation/05. Regression-Metrics-906P4BPnl9A.mp4 3.5 MB
Part 09-Module 01-Lesson 04_Hyperparameters/07. Number Of Hidden Units Layers-IkGAIQH5wH8.mp4 3.6 MB
Part 03-Module 01-Lesson 03_Hyperparameters/07. Number Of Hidden Units Layers-IkGAIQH5wH8.mp4 3.6 MB
Part 04-Module 02-Lesson 02_Hyperparameters/07. Number Of Hidden Units Layers-IkGAIQH5wH8.mp4 3.6 MB
Part 02-Module 04-Lesson 02_Intro to TensorFlow/21. 29 L Optimizing A Logistic Classifier-U_7nO1dm2tY.mp4 3.6 MB
Part 07-Module 01-Lesson 02_Implementing Gradient Descent/07. Backpropagation-MZL97-2joxQ.mp4 3.6 MB
Part 01-Module 03-Lesson 02_Intro to Neural Networks/15. Backpropagation-MZL97-2joxQ.mp4 3.6 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/14. Training Optimizers-AU5gH7LS57E.mp4 3.6 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/14. Training Optimizers-AU5gH7LS57E.mp4 3.6 MB
Part 01-Module 03-Lesson 02_Intro to Neural Networks/02. Logistic Regression - Question-kSs6O3R7JUI.mp4 3.6 MB
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/23. What Is The Neural Network Looking At-qN-rvoxPbBw.mp4 3.6 MB
Part 02-Module 05-Lesson 02_Convolutional Networks/img/screen-shot-2016-11-24-at-12.09.24-pm.png 3.7 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.09.24-pm.png 3.7 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/13. Error Functions-YfUUunxWIJw.mp4 3.7 MB
Part 09-Module 01-Lesson 03_Implementation of RNN and LSTM/08. LSTM Cell Solution-X4uA0dq_4jA.mp4 3.7 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/09. LSTM Cell Solution-X4uA0dq_4jA.mp4 3.7 MB
Part 09-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/02. RNN Vs LSTM-70MgF-IwAr8.mp4 3.8 MB
Part 02-Module 04-Lesson 02_Intro to TensorFlow/17. 17 L Transition Into Practical Aspects Of Learning-bKqkRFOOKoA.mp4 3.8 MB
Part 01-Module 03-Lesson 02_Intro to Neural Networks/01. Introducing Luis-nto-stLuN6M.mp4 3.8 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/10. 07 Perceptron Algorithm Trick-lif_qPmXvWA.mp4 3.8 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/24. Gradient Descent-rhVIF-nigrY.mp4 3.9 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/18. Maximum Likelihood 2-6nUUeQ9AeUA.mp4 4.0 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/05. Linear Boundaries-X-uMlsBi07k.mp4 4.0 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/13. MDPs, Part 1-NBWbluSbxPg.mp4 4.0 MB
Part 03-Module 07-Lesson 03_Translation Project/01. Machine Translation Intro-5thBwpcYoiI.mp4 4.0 MB
Part 04-Module 02-Lesson 03_Deep Convolutional GANs/08. Discriminator Solution-ffPWI2yJscw.mp4 4.1 MB
Part 10-Module 01-Lesson 02_Deep Convolutional GANs/08. Discriminator Solution-ffPWI2yJscw.mp4 4.1 MB
Part 09-Module 01-Lesson 05_Embeddings and Word2vec/05. Batches Solution-DdfR0RjSC-Q.mp4 4.1 MB
Part 03-Module 02-Lesson 01_Embeddings and Word2vec/05. Batches Solution-DdfR0RjSC-Q.mp4 4.1 MB
Part 02-Module 04-Lesson 02_Intro to TensorFlow/22. 30 L Stochastic Gradient Descent-U9iEGUd9kJ0.mp4 4.1 MB
Part 07-Module 01-Lesson 03_Training Neural Networks/13. Batch vs Stochastic Gradient Descent-2p58rVgqsgo.mp4 4.1 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/01. Intro To RNNs-64HSG6HAfEI.mp4 4.2 MB
Part 03-Module 05-Lesson 01_Transfer Learning in TensorFlow/08. Building The Classifier-6ifxRQ_gL7w.mp4 4.2 MB
Part 08-Module 01-Lesson 06_Transfer Learning in TensorFlow/08. Building The Classifier-6ifxRQ_gL7w.mp4 4.2 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/16. DL 18 Q Softmax V2-RC_A9Tu99y4.mp4 4.2 MB
Part 09-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/03. LSTM Basics-gjb68a4XsqE.mp4 4.2 MB
Part 01-Module 03-Lesson 01_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.mp4 4.2 MB
Part 06-Module 01-Lesson 05_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.mp4 4.2 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/01. Introducing Andrew Trask-ltO71Bm8b3M.mp4 4.3 MB
Part 02-Module 04-Lesson 02_Intro to TensorFlow/19. Normalized Inputs And Initial Weights-WaHQ9-UXIIg.mp4 4.3 MB
Part 03-Module 01-Lesson 03_Hyperparameters/08. RNN Hyperparameters-yQvnv7l_aUo.mp4 4.3 MB
Part 09-Module 01-Lesson 04_Hyperparameters/08. RNN Hyperparameters-yQvnv7l_aUo.mp4 4.3 MB
Part 04-Module 02-Lesson 02_Hyperparameters/08. RNN Hyperparameters-yQvnv7l_aUo.mp4 4.3 MB
Part 11-Module 01-Lesson 03_The RL Framework The Solution/06. Bellman Equations-UgIaDMvSdUo.mp4 4.3 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/22. DL 27 Multi-Class Cross Entropy 2 Fix-keDswcqkees.mp4 4.3 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/11. Model Optimizer Solution-_Qhz9SbR7xY.mp4 4.3 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/11. Model Optimizer Solution-_Qhz9SbR7xY.mp4 4.3 MB
Part 03-Module 02-Lesson 01_Embeddings and Word2vec/07. Negative Sampling-gW17AHBKbHY.mp4 4.4 MB
Part 09-Module 01-Lesson 05_Embeddings and Word2vec/07. Negative Sampling-gW17AHBKbHY.mp4 4.4 MB
Part 08-Module 01-Lesson 06_Transfer Learning in TensorFlow/09. Training The Classifier-b7Fy3cIoJ1Y.mp4 4.4 MB
Part 03-Module 05-Lesson 01_Transfer Learning in TensorFlow/09. Training The Classifier-b7Fy3cIoJ1Y.mp4 4.4 MB
Part 01-Module 02-Lesson 01_Regression/01. Welcome to Week One-10M2DnJuziE.mp4 4.4 MB
Part 07-Module 01-Lesson 03_Training Neural Networks/08. Dropout-Ty6K6YiGdBs.mp4 4.4 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/11. Building the Network-5sZkRSHfiAE.mp4 4.4 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/11. Building the Network-5sZkRSHfiAE.mp4 4.4 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/20. Cross Entropy 1-iREoPUrpXvE.mp4 4.4 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/11. Network Loss-itu-uNK4brc.mp4 4.5 MB
Part 09-Module 01-Lesson 03_Implementation of RNN and LSTM/10. Network Loss-itu-uNK4brc.mp4 4.5 MB
Part 11-Module 01-Lesson 06_Temporal-Difference Methods/13. TD Control Expected Sarsa-kEKupCyU0P0.mp4 4.5 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/12. Building the Network Solution-Ikp3rVzG970.mp4 4.5 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/12. Building the Network Solution-Ikp3rVzG970.mp4 4.5 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/06. The Reward Hypothesis-uAqNwgZ49JE.mp4 4.6 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/04. MLPs For Image Classification-TIFStebu530.mp4 4.6 MB
Part 08-Module 01-Lesson 06_Transfer Learning in TensorFlow/06. Data Preparation-WEtKkHlhhZA.mp4 4.6 MB
Part 03-Module 05-Lesson 01_Transfer Learning in TensorFlow/06. Data Preparation-WEtKkHlhhZA.mp4 4.6 MB
Part 03-Module 06-Lesson 01_Sequence to Sequence/04. Architecture encoder decoder-dkHdEAJnV_w.mp4 4.7 MB
Part 11-Module 01-Lesson 04_Dynamic Programming/04. Another Gridworld Example-n9SbomnLb-U.mp4 4.9 MB
Part 09-Module 01-Lesson 03_Implementation of RNN and LSTM/11. Output And Loss Solutions-CT8hcU7FmGc.mp4 4.9 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/12. Output And Loss Solutions-CT8hcU7FmGc.mp4 4.9 MB
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/02. 02 Skin Cancer V4-70jGZeiTNgk.mp4 5.0 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/32. Combinando modelos-Boy3zHVrWB4.mp4 5.0 MB
Part 09-Module 01-Lesson 04_Hyperparameters/05. Minibatch Size-GrrO1NFxaW8.mp4 5.0 MB
Part 03-Module 01-Lesson 03_Hyperparameters/05. Minibatch Size-GrrO1NFxaW8.mp4 5.0 MB
Part 04-Module 02-Lesson 02_Hyperparameters/05. Minibatch Size-GrrO1NFxaW8.mp4 5.0 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/23. Error Function-V5kkHldUlVU.mp4 5.1 MB
Part 07-Module 01-Lesson 03_Training Neural Networks/05. Model Complexity Graph-NnS0FJyVcDQ.mp4 5.1 MB
Part 11-Module 01-Lesson 05_Monte Carlo Methods/01. Introduction-W2EP3riQSus.mp4 5.2 MB
Part 11-Module 01-Lesson 08_RL in Continuous Spaces/13. Non-Linear Function Approximation-rITnmpD2mN8.mp4 5.2 MB
Part 11-Module 01-Lesson 10_Policy-Based Methods/01. M2L3 01 V1-YOSREyp04HA.mp4 5.2 MB
Part 02-Module 05-Lesson 02_Convolutional Networks/18. Explore the Design Space-FG7M9tWH2nQ.mp4 5.2 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/07. Getting Started with GANs-QA2ntKUha4g.mp4 5.3 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/07. Getting Started with GANs-QA2ntKUha4g.mp4 5.3 MB
Part 02-Module 01-Lesson 01_Model Evaluation and Validation/03. Confusion Matrix-Question-9GLNjmMUB_4.mp4 5.3 MB
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/24. Confusion Matrix-Question 1-9GLNjmMUB_4.mp4 5.3 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/07. Batching Data Solution-o3nBxHJLQcc.mp4 5.3 MB
Part 09-Module 01-Lesson 03_Implementation of RNN and LSTM/06. Batching Data Solution-o3nBxHJLQcc.mp4 5.3 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/07. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.mp4 5.4 MB
Part 11-Module 01-Lesson 01_Introduction to RL/01. Introduction-6jSFl5kxIBs.mp4 5.4 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/06. Model Validation in Keras-002jNXSM6CU.mp4 5.5 MB
Part 11-Module 01-Lesson 03_The RL Framework The Solution/05. State-Value Functions-llakAjwox_8.mp4 5.5 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/33. DL 41 Feedforward FIX V2-hVCuvMGOfyY.mp4 5.6 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/15. Discrete vs. Continuous-Rm2KxFaPiJg.mp4 5.6 MB
Part 05-Module 01-Lesson 01_Enroll in your next Nanodegree program/img/carnd.jpg 5.6 MB
Part 03-Module 06-Lesson 01_Sequence to Sequence/05. Architecture in More Depth-rdAo4MqLbEk.mp4 5.6 MB
Part 11-Module 01-Lesson 03_The RL Framework The Solution/01. Introduction-9Wyf5Zsska8.mp4 5.7 MB
Part 02-Module 01-Lesson 01_Model Evaluation and Validation/07. Model Complexity Graph-Question-YS5OQCA5cLY.mp4 5.7 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/05. Categorical Cross-Entropy-3sDYifgjFck.mp4 5.7 MB
Part 08-Module 01-Lesson 03_Weight Initialization/04. Weight Initialization 3-JIQl0jMpdsI.mp4 5.7 MB
Part 03-Module 04-Lesson 02_Weight Initialization/04. Weight Initialization 3-JIQl0jMpdsI.mp4 5.7 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/08. Training The Network -P-LXQPVXl4A.mp4 5.7 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/08. Training The Network -P-LXQPVXl4A.mp4 5.7 MB
Part 02-Module 04-Lesson 02_Intro to TensorFlow/20. 21 L Measuring Performance-byP0DJImOSk.mp4 5.8 MB
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/12. Validating The Training-Oxm9ofvov3I.mp4 5.8 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/07. When do MLPs (not) work well-deMeuLdZN3Q.mp4 5.8 MB
Part 02-Module 01-Lesson 01_Model Evaluation and Validation/02. Testing-gmxGRJSKEb0.mp4 5.9 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/34. DL 46 Calculating The Gradient 2 V2 (2)-7lidiTGIlN4.mp4 6.0 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/18. Maximum Likelihood 1-1yJx-QtlvNI.mp4 6.0 MB
Part 02-Module 04-Lesson 02_Intro to TensorFlow/02. What Is Deep Learning-INt1nULYPak.mp4 6.1 MB
Part 03-Module 06-Lesson 01_Sequence to Sequence/02. Jay's Introduction-HPOzAlXhuxQ.mp4 6.1 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/15. Pooling Layers-OkkIZNs7Cyc.mp4 6.1 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/13. Training Losses-IaAeDrXMEcU.mp4 6.1 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/13. Training Losses-IaAeDrXMEcU.mp4 6.1 MB
Part 06-Module 01-Lesson 01_Welcome to Deep Learning/02. Meet Your Instructors--UOFRxCu414.mp4 6.1 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/03. Introducing Semi-Supervised Learning-tnCClNy5z5c.mp4 6.2 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/03. Introducing Semi-Supervised Learning-tnCClNy5z5c.mp4 6.2 MB
Part 06-Module 01-Lesson 05_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.mp4 6.2 MB
Part 01-Module 03-Lesson 01_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.mp4 6.2 MB
Part 11-Module 01-Lesson 03_The RL Framework The Solution/08. Optimality-j231aRV74QM.mp4 6.3 MB
Part 11-Module 01-Lesson 11_Actor-Critic Methods/03. RL M2L4 03 Two Function Approximators V1-37KQEgLaLfw.mp4 6.4 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/04. Data Prep-P5hOx09mwaM.mp4 6.4 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/04. Data Prep-P5hOx09mwaM.mp4 6.4 MB
Part 06-Module 01-Lesson 01_Welcome to Deep Learning/05. Projects You will Build-PqpdX7YxTlU.mp4 6.5 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/03. How Computers Interpret Images-V4f6p6uRhu8.mp4 6.5 MB
Part 11-Module 01-Lesson 04_Dynamic Programming/01. Introduction-ek2PD9RDrWw.mp4 6.5 MB
Part 01-Module 03-Lesson 03_Your first neural network/01. Introduction to the Project-dOwEDeJp8yw.mp4 6.5 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/10. Generator and Discriminator Solutions-9By2pAck044.mp4 6.6 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/10. Generator and Discriminator Solutions-9By2pAck044.mp4 6.6 MB
Part 07-Module 01-Lesson 03_Training Neural Networks/04. Underfitting And Overfitting-xj4PlXMsN-Y.mp4 6.7 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/34. Backpropagation V2-1SmY3TZTyUk.mp4 6.8 MB
Part 02-Module 01-Lesson 01_Model Evaluation and Validation/06. 04 L Types Of Errors-Twf1qnPZeSY.mp4 6.9 MB
Part 01-Module 01-Lesson 01_Welcome/09. Getting-Setup-1SuxTnuQkeE.mp4 6.9 MB
Part 06-Module 01-Lesson 01_Welcome to Deep Learning/10. Getting-Setup-1SuxTnuQkeE.mp4 6.9 MB
Part 11-Module 01-Lesson 03_The RL Framework The Solution/09. Action-Value Functions-KJLaRfOOPGA.mp4 6.9 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/21. CrossEntropy V1-1BnhC6e0TFw.mp4 6.9 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/07. Transforming Text into Numbers-7rHBU5cbePE.mp4 7.0 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/08. Transforming Text into Numbers-7rHBU5cbePE.mp4 7.0 MB
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/18. ROC Curve-2Iw5TiGzJI4.mp4 7.0 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/14. MDPs, Part 2-CUTtQvxKkNw.mp4 7.2 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/15. Training Losses and Optimizers Solutions-HlABZ9Q7xEo.mp4 7.2 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/15. Training Losses and Optimizers Solutions-HlABZ9Q7xEo.mp4 7.2 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/07. Goals and Rewards, Part 1-XPnj3Ya3EuM.mp4 7.2 MB
Part 01-Module 01-Lesson 01_Welcome/08. We Value Your Feedback-Dl23R0YCQ0U.mp4 7.2 MB
Part 09-Module 01-Lesson 06_Sentiment Prediction RNN/03. Data Preprocessing-h4-LwZU9_k8.mp4 7.2 MB
Part 03-Module 04-Lesson 03_Sentiment Prediction RNN/03. Data Preprocessing-h4-LwZU9_k8.mp4 7.2 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/02. LSTMs-RYbSHogZetc.mp4 7.2 MB
Part 11-Module 01-Lesson 05_Monte Carlo Methods/09. Generalized Policy Iteration-XRmz4nolEsw.mp4 7.3 MB
Part 11-Module 01-Lesson 01_Introduction to RL/05. Resources-_YPqfAnCqtk.mp4 7.3 MB
Part 10-Module 01-Lesson 02_Deep Convolutional GANs/10. Hyperparameters Solution-Rt8MlVDtpi8.mp4 7.3 MB
Part 04-Module 02-Lesson 03_Deep Convolutional GANs/10. Hyperparameters Solution-Rt8MlVDtpi8.mp4 7.3 MB
Part 01-Module 01-Lesson 01_Welcome/04. The first week-krK-TcGoYUI.mp4 7.4 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/08. Generator Network-btHVXnICmzQ.mp4 7.4 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/08. Generator Network-btHVXnICmzQ.mp4 7.4 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/13. Build The Network-RVNjDlWTBQU.mp4 7.4 MB
Part 09-Module 01-Lesson 03_Implementation of RNN and LSTM/12. Build The Network-RVNjDlWTBQU.mp4 7.4 MB
Part 11-Module 01-Lesson 03_The RL Framework The Solution/11. Optimal Policies-2rguYpVyCto.mp4 7.5 MB
Part 06-Module 01-Lesson 04_Jupyter Notebooks/02. Jupyter-qiYDWFLyXvg.mp4 7.5 MB
Part 01-Module 01-Lesson 03_Jupyter Notebooks/02. Jupyter-qiYDWFLyXvg.mp4 7.5 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/12. Trained Semi-Supervised GAN-9yWYZDX8-O8.mp4 7.5 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/12. Trained Semi-Supervised GAN-9yWYZDX8-O8.mp4 7.5 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/13. Wrap Up-x6JggcDTcys.mp4 7.6 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/14. Error Functions-jfKShxGAbok.mp4 7.6 MB
Part 04-Module 02-Lesson 03_Deep Convolutional GANs/06. Generator Solution-jyPwUEZg05Q.mp4 7.6 MB
Part 10-Module 01-Lesson 02_Deep Convolutional GANs/06. Generator Solution-jyPwUEZg05Q.mp4 7.6 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/24. RNN Summary-nXP0oGGRrO8.mp4 7.6 MB
Part 03-Module 02-Lesson 01_Embeddings and Word2vec/08. Building The Network Solution-pkBAhQ2Ki-8.mp4 7.7 MB
Part 09-Module 01-Lesson 05_Embeddings and Word2vec/08. Building The Network Solution-pkBAhQ2Ki-8.mp4 7.7 MB
Part 01-Module 03-Lesson 01_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2-8jtk8BzBdj8.mp4 7.7 MB
Part 06-Module 01-Lesson 05_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2-8jtk8BzBdj8.mp4 7.7 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/02. The Setting, Revisited-V6Q1uF8a6kA.mp4 7.7 MB
Part 01-Module 03-Lesson 02_Intro to Neural Networks/03. Logistic Regression - Solution-1iNylA3fJDs.mp4 7.7 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/09. Discriminator Solution-_X8ssUzu_Bo.mp4 7.8 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/09. Discriminator Solution-_X8ssUzu_Bo.mp4 7.8 MB
Part 07-Module 01-Lesson 01_Introduction to Neural Networks/02. Introduction-tn-CrUTkCUc.mp4 7.9 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/img/chess-game.jpg 7.9 MB
Part 07-Module 01-Lesson 03_Training Neural Networks/07. Regularization-ndYnUrx8xvs.mp4 7.9 MB
Part 11-Module 01-Lesson 06_Temporal-Difference Methods/07. TD Control Sarsa(0)-LkFkjfsRpXc.mp4 8.0 MB
Part 11-Module 01-Lesson 10_Policy-Based Methods/08. M2L3 08 V1-og3W6CXn1F0.mp4 8.0 MB
Part 03-Module 02-Lesson 01_Embeddings and Word2vec/04. Making Batches-jx7qwdw-94k.mp4 8.1 MB
Part 09-Module 01-Lesson 05_Embeddings and Word2vec/04. Making Batches-jx7qwdw-94k.mp4 8.1 MB
Part 11-Module 01-Lesson 01_Introduction to RL/03. The Setting-nh8Gwdu19nc.mp4 8.1 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/08. LSTM Cell-ajC-5uWB8S4.mp4 8.2 MB
Part 09-Module 01-Lesson 03_Implementation of RNN and LSTM/07. LSTM Cell-ajC-5uWB8S4.mp4 8.2 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/12. Stride and Padding-0r9o8hprDXQ.mp4 8.4 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/10. Convolutional Layers-h5R_JvdUrUI.mp4 8.4 MB
Part 02-Module 03-Lesson 01_MiniFlow/01. Miniflow Introduction-Nqp_UifEwt0.mp4 8.4 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/08. Goals and Rewards, Part 2-pVIFc72VYH8.mp4 8.4 MB
Part 10-Module 01-Lesson 02_Deep Convolutional GANs/09. Building And Training The Network-nXKk9GI4X14.mp4 8.5 MB
Part 04-Module 02-Lesson 03_Deep Convolutional GANs/09. Building And Training The Network-nXKk9GI4X14.mp4 8.5 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/22. Groundbreaking CNN Architectures-ddrB-mhMfkY.mp4 8.5 MB
Part 09-Module 01-Lesson 05_Embeddings and Word2vec/06. Building The Network-fhSb5c6UX6M.mp4 8.5 MB
Part 03-Module 02-Lesson 01_Embeddings and Word2vec/06. Building The Network-fhSb5c6UX6M.mp4 8.5 MB
Part 11-Module 01-Lesson 04_Dynamic Programming/17. Policy Iteration-gqv7o1kBDc0.mp4 8.5 MB
Part 08-Module 01-Lesson 07_Deep Learning for Cancer Detection with Sebastian Thrun/26. Conclusion-WhpE_8sTt-0.mp4 8.6 MB
Part 08-Module 01-Lesson 06_Transfer Learning in TensorFlow/10. Training And Testing-NLPtmQjGYCA.mp4 8.6 MB
Part 03-Module 05-Lesson 01_Transfer Learning in TensorFlow/10. Training And Testing-NLPtmQjGYCA.mp4 8.6 MB
Part 10-Module 01-Lesson 02_Deep Convolutional GANs/02. Deconvolution-sX_AxtB6CHI.mp4 8.7 MB
Part 04-Module 02-Lesson 03_Deep Convolutional GANs/02. Deconvolution-sX_AxtB6CHI.mp4 8.7 MB
Part 08-Module 01-Lesson 06_Transfer Learning in TensorFlow/02. Transfer Learning--WmQwYr0DYjY.mp4 8.7 MB
Part 03-Module 05-Lesson 01_Transfer Learning in TensorFlow/02. Transfer Learning--WmQwYr0DYjY.mp4 8.7 MB
Part 02-Module 05-Lesson 01_Deep Neural Networks/08. Regularization Intro-pECnr-5F3_Q.mp4 8.7 MB
Part 03-Module 04-Lesson 03_Sentiment Prediction RNN/06. Training The Network-nknJ3Xu3ld0.mp4 8.8 MB
Part 09-Module 01-Lesson 06_Sentiment Prediction RNN/06. Training The Network-nknJ3Xu3ld0.mp4 8.8 MB
Part 02-Module 05-Lesson 02_Convolutional Networks/04. Convolutional Networks-ISHGyvsT0QY.mp4 8.8 MB
Part 11-Module 01-Lesson 01_Introduction to RL/02. Applications-CV6B84mKRNM.mp4 8.9 MB
Part 02-Module 05-Lesson 01_Deep Neural Networks/01. Mat HS-9P7UPWFu8w8.mp4 8.9 MB
Part 03-Module 08-Lesson 02_Autoencoders/04. Simple Autoencoder Solution-Nv_D6DHfEk8.mp4 9.0 MB
Part 08-Module 01-Lesson 05_Autoencoders/04. Simple Autoencoder Solution-Nv_D6DHfEk8.mp4 9.0 MB
Part 11-Module 01-Lesson 11_Actor-Critic Methods/02. RL M2L4 02 A Better Score Function V2-_HBJ3l10-OE.mp4 9.1 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/18. CNNs in Keras Practical Example-faFvmGDwXX0.mp4 9.1 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/10. Model Loss Solution-r3DtohmychE.mp4 9.3 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/10. Model Loss Solution-r3DtohmychE.mp4 9.3 MB
Part 03-Module 05-Lesson 01_Transfer Learning in TensorFlow/03. Building VGGNet-615SslQiGvo.mp4 9.3 MB
Part 08-Module 01-Lesson 06_Transfer Learning in TensorFlow/03. Building VGGNet-615SslQiGvo.mp4 9.3 MB
Part 03-Module 06-Lesson 01_Sequence to Sequence/06. Preprocessing-ktQW6p9pOS4.mp4 9.3 MB
Part 01-Module 01-Lesson 01_Welcome/02. Projects You Will Build-yDPuDuCMST8.mp4 9.3 MB
Part 11-Module 01-Lesson 08_RL in Continuous Spaces/12. Kernel Functions-RdkPVYyVOvU.mp4 9.3 MB
Part 09-Module 01-Lesson 03_Implementation of RNN and LSTM/09. RNN Output-RkanDkcrTxs.mp4 9.4 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/10. RNN Output-RkanDkcrTxs.mp4 9.4 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/01. Intro to Deep Q-Learning-o3cmuUDhP3I.mp4 9.5 MB
Part 06-Module 01-Lesson 05_Matrix Math and NumPy Refresher/09. Matrix Transposes-NVK5xCY3CZE.mp4 9.5 MB
Part 01-Module 03-Lesson 01_Matrix Math and NumPy Refresher/09. Matrix Transposes-NVK5xCY3CZE.mp4 9.5 MB
Part 11-Module 01-Lesson 05_Monte Carlo Methods/12. MC Control Policy Evaluation-3_opwMzpEEI.mp4 9.5 MB
Part 02-Module 04-Lesson 02_Intro to TensorFlow/03. Solving Problems - Big And Small-WHcRQMGSbqg.mp4 9.6 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/23. Visualizing CNNs-mnqS_EhEZVg.mp4 9.6 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/09. Mini Project 2 Solution-45ihpPaeO8E.mp4 9.7 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/10. Mini Project 2 Solution-45ihpPaeO8E.mp4 9.7 MB
Part 02-Module 01-Lesson 01_Model Evaluation and Validation/07. Model-Complexity-Graph Solution 2-5pWHGkNyRhA.mp4 9.7 MB
Part 08-Module 01-Lesson 06_Transfer Learning in TensorFlow/05. Data Preparation-WfsDMq-b3y4.mp4 9.7 MB
Part 03-Module 05-Lesson 01_Transfer Learning in TensorFlow/05. Data Preparation-WfsDMq-b3y4.mp4 9.7 MB
Part 11-Module 01-Lesson 01_Introduction to RL/04. OpenAI Gym-MktEOWp3QLg.mp4 9.9 MB
Part 03-Module 04-Lesson 02_Weight Initialization/05. Weight Initialization 4-FM6t7AsodGQ.mp4 10.0 MB
Part 08-Module 01-Lesson 03_Weight Initialization/05. Weight Initialization 4-FM6t7AsodGQ.mp4 10.0 MB
Part 03-Module 01-Lesson 03_Hyperparameters/03. Learning Rate-HLMjeDez7ps.mp4 10.1 MB
Part 04-Module 02-Lesson 02_Hyperparameters/03. Learning Rate-HLMjeDez7ps.mp4 10.1 MB
Part 09-Module 01-Lesson 04_Hyperparameters/03. Learning Rate-HLMjeDez7ps.mp4 10.1 MB
Part 03-Module 02-Lesson 01_Embeddings and Word2vec/03. Subsampling Solution-MAUM_mV_lj8.mp4 10.1 MB
Part 09-Module 01-Lesson 05_Embeddings and Word2vec/03. Subsampling Solution-MAUM_mV_lj8.mp4 10.1 MB
Part 11-Module 01-Lesson 06_Temporal-Difference Methods/06. TD Prediction Action Values-1c029-7_9GA.mp4 10.2 MB
Part 03-Module 02-Lesson 01_Embeddings and Word2vec/09. Training Results-uISA5ns47s8.mp4 10.3 MB
Part 09-Module 01-Lesson 05_Embeddings and Word2vec/09. Training Results-uISA5ns47s8.mp4 10.3 MB
Part 11-Module 01-Lesson 08_RL in Continuous Spaces/14. Summary-MTEBk43oByU.mp4 10.4 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/10. Cumulative Reward-ysriH65lV9o.mp4 10.4 MB
Part 11-Module 01-Lesson 11_Actor-Critic Methods/04. RL M2L4 04 The Actor And The Critic V1-bvbE9F7urd4.mp4 10.5 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/03. Episodic vs. Continuing Tasks-E1I-BPanSM8.mp4 10.6 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/02. Semi-Supervised Learning-_LRpHPxZaX0.mp4 10.6 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/02. Semi-Supervised Learning-_LRpHPxZaX0.mp4 10.6 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/11. Building a Neural Network-aM2k7RTjjJI.mp4 10.7 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/10. Building a Neural Network-aM2k7RTjjJI.mp4 10.7 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/20. Image Augmentation in Keras-odStujZq3GY.mp4 10.8 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/03. Other Generative Models, How GANs Work-MF0QCP1OC9I.mp4 10.8 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/03. Other Generative Models, How GANs Work-MF0QCP1OC9I.mp4 10.8 MB
Part 06-Module 01-Lesson 03_Anaconda/02. Why Anaconda-VXukXZv7SCQ.mp4 10.8 MB
Part 01-Module 01-Lesson 02_Anaconda/02. Why Anaconda-VXukXZv7SCQ.mp4 10.8 MB
Part 11-Module 01-Lesson 08_RL in Continuous Spaces/09. Coarse Coding-Uu1J5KLAfTU.mp4 10.8 MB
Part 11-Module 01-Lesson 11_Actor-Critic Methods/01. RL M2L4 01 Actor Critic Methods RENDER V1 V1-FXhyxJzgt8U.mp4 10.9 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/03. Monte Carlo Learning-qOviWYwcvsg.mp4 10.9 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/12. 14 RNN A V4 Final-ofbnDxGSUcg.mp4 10.9 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/14. 17 RNN Unfolded V3 Final-xLIA_PTWXog.mp4 11.0 MB
Part 03-Module 07-Lesson 01_Reinforcement Learning/03. 02 Q-Learning-WQgdnzzhSLM.mp4 11.1 MB
Part 06-Module 01-Lesson 05_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.mp4 11.1 MB
Part 01-Module 03-Lesson 01_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.mp4 11.1 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/01. 00 Luis Introducing Ortal Newtitle121217-oXv7GiC-jrM.mp4 11.2 MB
Part 11-Module 01-Lesson 11_Actor-Critic Methods/05. RL M2L4 05 Advantage Function RENDER V1 V2-vpLmzKqcgfc.mp4 11.2 MB
Part 08-Module 01-Lesson 03_Weight Initialization/02. Weight Initialization 1-6vXMYu_TQIA.mp4 11.3 MB
Part 03-Module 04-Lesson 02_Weight Initialization/02. Weight Initialization 1-6vXMYu_TQIA.mp4 11.3 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/01. Introducing Andrew Trask-U3PqQF-8qyI.mp4 11.3 MB
Part 11-Module 01-Lesson 08_RL in Continuous Spaces/07. Tile Coding-BRs7AnTZ_8k.mp4 11.6 MB
Part 03-Module 03-Lesson 01_TensorBoard/03. TensorBoard Graphs 2-REmz7HUj6f4.mp4 11.6 MB
Part 03-Module 04-Lesson 02_Weight Initialization/03. Weight Initialization 2-BI3f0Cdc_nU.mp4 11.6 MB
Part 08-Module 01-Lesson 03_Weight Initialization/03. Weight Initialization 2-BI3f0Cdc_nU.mp4 11.6 MB
Part 03-Module 04-Lesson 03_Sentiment Prediction RNN/02. Sentiment Prediction-uGN3rZJRiMY.mp4 11.8 MB
Part 09-Module 01-Lesson 06_Sentiment Prediction RNN/02. Sentiment Prediction-uGN3rZJRiMY.mp4 11.8 MB
Part 01-Module 03-Lesson 02_Intro to Neural Networks/11. Gradient Descent-Math-7sxA5Ap8AWM.mp4 11.8 MB
Part 07-Module 01-Lesson 02_Implementing Gradient Descent/03. Gradient Descent-Math-7sxA5Ap8AWM.mp4 11.8 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/16. A Trained GAN-TR-uEJcjig4.mp4 12.2 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/16. A Trained GAN-TR-uEJcjig4.mp4 12.2 MB
Part 02-Module 02-Lesson 02_Intro to TFLearn/04. TFLearn-YF7S6hi4bnc.mp4 12.3 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/23. Andrew Trask - Outro-nIF0GLOQglQ.mp4 12.4 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/22. Andrew Trask - Outro-nIF0GLOQglQ.mp4 12.4 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/02. Cool Things To Do With GANs-bo-ToTdhgew.mp4 12.6 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/02. Cool Things To Do With GANs-bo-ToTdhgew.mp4 12.6 MB
Part 03-Module 03-Lesson 01_TensorBoard/02. TensorBoard Graphs 1-M64FWxf1yK4.mp4 12.6 MB
Part 11-Module 01-Lesson 05_Monte Carlo Methods/18. MC Control Constant-alpha-QFV1nI9Zpoo.mp4 13.1 MB
Part 11-Module 01-Lesson 08_RL in Continuous Spaces/05. Discretization-j2eZyUpy--E.mp4 13.2 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/07. Model Optimization Exercise-wNpI1wUA4Io.mp4 13.3 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/07. Model Optimization Exercise-wNpI1wUA4Io.mp4 13.3 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/02. Neural Nets as Value Functions-cBi7vLrk8QQ.mp4 13.3 MB
Part 03-Module 08-Lesson 02_Autoencoders/06. Convolutional Autoencoder Solutions-w3iPs6YnqmY.mp4 13.3 MB
Part 08-Module 01-Lesson 05_Autoencoders/06. Convolutional Autoencoder Solutions-w3iPs6YnqmY.mp4 13.3 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/08. 13 Overfitting Intro V4 Final-rmBLnVbFfFY.mp4 13.4 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/26. Transfer Learning in Keras-HsIAznMM1LA.mp4 13.6 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/09. Local Connectivity-z9wiDg0w-Dc.mp4 13.7 MB
Part 09-Module 01-Lesson 03_Implementation of RNN and LSTM/13. Build The Network And Results-hu8iMMqajmQ.mp4 13.9 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/14. Build The Network And Results-hu8iMMqajmQ.mp4 13.9 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/25. Transfer Learning-LHG5FltaR6I.mp4 14.0 MB
Part 01-Module 01-Lesson 01_Welcome/03. Meet Your Instructors -EcP0U4720sA.mp4 14.0 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/04. Games, Equilibrium, GANs Solution Render-2zi8DOWIVas.mp4 14.1 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/04. Games, Equilibrium, GANs Solution Render-2zi8DOWIVas.mp4 14.1 MB
Part 03-Module 01-Lesson 01_Intro to Recurrent Neural Networks/06. Implementing a Character-wise RNN-KPCMn_jg2oY.mp4 14.3 MB
Part 09-Module 01-Lesson 03_Implementation of RNN and LSTM/05. Implementing a Character-wise RNN-KPCMn_jg2oY.mp4 14.3 MB
Part 11-Module 01-Lesson 04_Dynamic Programming/20. Truncated Policy Iteration-a-RvCxlPMho.mp4 14.8 MB
Part 06-Module 01-Lesson 01_Welcome to Deep Learning/01. 01 Welcome To The Deep Learning Program-3QPEmwq2NaE.mp4 15.0 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/11. Discounted Return-opXGNPwwn7g.mp4 15.0 MB
Part 03-Module 03-Lesson 01_TensorBoard/05. TensorBoard Hyperparameters-THiwPbkjoLQ.mp4 15.1 MB
Part 11-Module 01-Lesson 02_The RL Framework The Problem/17. MDPs, Part 3-UlXHFbla3QI.mp4 15.5 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/09. 10 Backpropagation Example A V3 Final-3k72z_WaeXg.mp4 15.5 MB
Part 01-Module 03-Lesson 02_Intro to Neural Networks/04. Neural Networks-Mqogpnp1lrU.mp4 15.6 MB
Part 11-Module 01-Lesson 04_Dynamic Programming/23. Value Iteration-XNeQn8N36y8.mp4 16.4 MB
Part 03-Module 08-Lesson 02_Autoencoders/03. A-Simple-Autoencoders 21718-lXGdkCT8E1c.mp4 16.4 MB
Part 08-Module 01-Lesson 05_Autoencoders/03. A-Simple-Autoencoders 21718-lXGdkCT8E1c.mp4 16.4 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/06. Model Loss Exercise-W7TawMNxBds.mp4 16.6 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/06. Model Loss Exercise-W7TawMNxBds.mp4 16.6 MB
Part 10-Module 01-Lesson 01_Generative Adversarial Networks/05. GANs Architecture -gaEs7ccZv_Q.mp4 16.7 MB
Part 04-Module 01-Lesson 01_Generative Adversarial Networks/05. GANs Architecture -gaEs7ccZv_Q.mp4 16.7 MB
Part 10-Module 01-Lesson 02_Deep Convolutional GANs/05. DCGAN And The Generator-CH6BxLTKt7s.mp4 16.8 MB
Part 04-Module 02-Lesson 03_Deep Convolutional GANs/05. DCGAN And The Generator-CH6BxLTKt7s.mp4 16.8 MB
Part 11-Module 01-Lesson 06_Temporal-Difference Methods/10. TD Control Sarsamax-4DxoYuR7aZ4.mp4 17.3 MB
Part 11-Module 01-Lesson 10_Policy-Based Methods/05. M2L3 05 V1-eZxxNNIZuwA.mp4 17.5 MB
Part 11-Module 01-Lesson 11_Actor-Critic Methods/07. Summary-hvYQ_3LgCYs.mp4 17.7 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/04. Temporal Difference Learning-lpmDi0QeUm8.mp4 17.8 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/19. 21 RNN BPTT C V7 Final-uBy_eIJDD1M.mp4 18.1 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/04. 03 RNN Applications V3 Final-6JbTNARuKII.mp4 18.1 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/05. Q-Learning-AI5gLgYMSq8.mp4 18.2 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/09. Deep Q-Learning Algorithm-MqTXoCxQ_eY.mp4 18.3 MB
Part 02-Module 02-Lesson 02_Intro to TFLearn/05. Sentiment Analysis Solution SC-s7FKYC5Zcm8.mp4 18.4 MB
Part 01-Module 01-Lesson 01_Welcome/01. Welcome-PdPdogFHnvE.mp4 18.4 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/04. Framing the Problem-IsTOnkAKaJw.mp4 18.5 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/05. Framing the Problem-IsTOnkAKaJw.mp4 18.5 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/02. Applications of CNNs-HrYNL_1SV2Y.mp4 18.6 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/06. 06 FeedForward A V7 Final-4rCfnWbx8-0.mp4 18.6 MB
Part 04-Module 02-Lesson 05_Semi-Supervised Learning/05. Building The Generator And Discriminator-OWytckbbeGQ.mp4 18.8 MB
Part 10-Module 01-Lesson 03_Semi-Supervised Learning/05. Building The Generator And Discriminator-OWytckbbeGQ.mp4 18.8 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/18. 20 RNN BPTT B V5 Final-bUU9BEQw0IA.mp4 19.0 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/17. CNNs For Image Classification-l9vg_1YUlzg.mp4 19.0 MB
Part 11-Module 01-Lesson 10_Policy-Based Methods/03. M2L3 03 V2-TePX-0Bs23E.mp4 19.8 MB
Part 03-Module 03-Lesson 01_TensorBoard/04. TensorBoard Variables 1-QG41p4Wx5wc.mp4 19.9 MB
Part 03-Module 04-Lesson 03_Sentiment Prediction RNN/05. Building The RNN 1-XTD6slf64fM.mp4 20.0 MB
Part 09-Module 01-Lesson 06_Sentiment Prediction RNN/05. Building The RNN 1-XTD6slf64fM.mp4 20.0 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/05. 05 RNN FFNN Reminder B V6 Final-FfPjaGcZODc.mp4 20.6 MB
Part 08-Module 01-Lesson 04_Convolutional Neural Networks/11. Convolutional Layers-RnM1D-XI--8.mp4 20.8 MB
Part 11-Module 01-Lesson 05_Monte Carlo Methods/10. MC Control Incremental Mean-E2RITH-2NUE.mp4 21.0 MB
Part 11-Module 01-Lesson 08_RL in Continuous Spaces/10. Function Approximation-UTGWVY6jEdg.mp4 21.1 MB
Part 11-Module 01-Lesson 03_The RL Framework The Solution/02. Policies-hc3LrvaC13U.mp4 21.2 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/16. Understanding Inefficiencies in our Network-4MuS-6ATxCU.mp4 21.7 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/15. Understanding Inefficiencies in our Network-4MuS-6ATxCU.mp4 21.7 MB
Part 11-Module 01-Lesson 06_Temporal-Difference Methods/01. Introduction-yXErXQulI_o.mp4 21.7 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/02. 01 RNN Intro V6 Final-AIQEqg6F38A.mp4 21.9 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/08. Fixed Q Targets-SWpyiEezfp4.mp4 22.0 MB
Part 11-Module 01-Lesson 10_Policy-Based Methods/04. M2L3 04 V1-QicxmyE5vTo.mp4 22.0 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/13. 16 RNN B V4 Final-wsif3p5t7CI.mp4 22.1 MB
Part 11-Module 01-Lesson 08_RL in Continuous Spaces/03. Discrete vs. Continuous Spaces-uHstLeRzaE8.mp4 22.4 MB
Part 08-Module 01-Lesson 05_Autoencoders/05. Convolutional Autoencoders-18SZVRaumGs.mp4 22.6 MB
Part 03-Module 08-Lesson 02_Autoencoders/05. Convolutional Autoencoders-18SZVRaumGs.mp4 22.6 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/17. 19 RNN BPTT A V6 Final-eE2L3-2wKac.mp4 22.6 MB
Part 11-Module 01-Lesson 05_Monte Carlo Methods/13. MC Control Policy Improvement-2RKH-BInX7s.mp4 23.1 MB
Part 11-Module 01-Lesson 05_Monte Carlo Methods/06. MC Prediction Action Values-08tLtbh0xLs.mp4 23.1 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/16. 18 RNN Example V5 Final-MDLk3fhpTx0.mp4 23.2 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/18. Further Noise Reduction-Kl3hWxizKVg.mp4 23.4 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/19. Further Noise Reduction-Kl3hWxizKVg.mp4 23.4 MB
Part 09-Module 01-Lesson 06_Sentiment Prediction RNN/07. Sentiment RNN 2-V9YGGjmoHS0.mp4 24.2 MB
Part 03-Module 04-Lesson 03_Sentiment Prediction RNN/07. Sentiment RNN 2-V9YGGjmoHS0.mp4 24.2 MB
Part 09-Module 01-Lesson 05_Embeddings and Word2vec/02. Implementing Word2Vec-7M431_f9HgE.mp4 24.5 MB
Part 03-Module 02-Lesson 01_Embeddings and Word2vec/02. Implementing Word2Vec-7M431_f9HgE.mp4 24.5 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/02. Andrew Trask - Intro-da1I0mea1jQ.mp4 24.9 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/02. Andrew Trask - Intro-da1I0mea1jQ.mp4 24.9 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/03. 02 RNN History V4 Final-HbxAnYUfRnc.mp4 25.4 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/06. Mini Project 1 Solution-l4r5l0HvHRI.mp4 26.0 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/07. Mini Project 1 Solution-l4r5l0HvHRI.mp4 26.0 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/06. Deep Q Network-GgtR_d1OB-M.mp4 26.9 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/05. 04 RNN FFNN Reminder A V7 Final-_vrp2lZjXf0.mp4 27.0 MB
Part 11-Module 01-Lesson 04_Dynamic Programming/08. Iterative Policy Evaluation-eDXIL_oOJHI.mp4 27.9 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/06. 07 FeedForward B V3-kTYbTVh1d0k.mp4 27.9 MB
Part 03-Module 03-Lesson 02_Siraj's Music Generation/02. How to Succeed in any Programming Interview-5KB5KAak6tM.mp4 28.3 MB
Part 11-Module 01-Lesson 04_Dynamic Programming/05. An Iterative Method-AX-hG3KvwzY.mp4 28.9 MB
Part 11-Module 01-Lesson 08_RL in Continuous Spaces/11. Linear Function Approximation-OJ5wrB7o-pI.mp4 30.1 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/17. Mini Project 5 Solution-Hv86B_jjWTI.mp4 30.3 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/18. Mini Project 5 Solution-Hv86B_jjWTI.mp4 30.3 MB
Part 11-Module 01-Lesson 06_Temporal-Difference Methods/03. TD Prediction TD(0)-CsD6b0csU7o.mp4 31.6 MB
Part 11-Module 01-Lesson 04_Dynamic Programming/14. Policy Improvement-4_adUEK0IHg.mp4 31.9 MB
Part 11-Module 01-Lesson 10_Policy-Based Methods/02. M2L3 02 V2-ToS8vXGdODE.mp4 34.1 MB
Part 11-Module 01-Lesson 08_RL in Continuous Spaces/01. Deep Reinforcement Learning-GPjK124RU5g.mp4 34.8 MB
Part 11-Module 01-Lesson 05_Monte Carlo Methods/03. MC Prediction State Values-0q2wSWyuBj8.mp4 35.0 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/21. Analysis What's Going on in the Weights-UHsT35pbpcE.mp4 35.3 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/22. Analysis What's Going on in the Weights-UHsT35pbpcE.mp4 35.3 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/08. 08 Backpropagation Theory V6 Final-Xlgd8I3TWUg.mp4 36.5 MB
Part 04-Module 02-Lesson 01_Siraj's One-Shot Learning/01. How to Learn from Little Data - Intro to Deep Learning #17-tChcZpBbTTA.mp4 37.1 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/25. 23 From RNNs To LSTMs V4 Final-MsqybcWmzGY.mp4 37.9 MB
Part 03-Module 04-Lesson 01_Siraj's Text Summarization/01. How to Make a Text Summarizer - Intro to Deep Learning #10-ogrJaOIuBx4.mp4 38.0 MB
Part 03-Module 05-Lesson 02_Siraj's Language Translation/01. How to Make a Language Translator - Intro to Deep Learning #11-nRBnh4qbPHI.mp4 38.3 MB
Part 09-Module 01-Lesson 01_Recurrent Neural Networks/10. 12 Backpropagation Example B V6 Final-yiSwuMP2UIA.mp4 38.9 MB
Part 01-Module 01-Lesson 04_Applying Deep Learning/03. Traffic Navigation with Deep Reinforcement Learning-az5ElmV4DhY.mp4 40.0 MB
Part 06-Module 01-Lesson 02_Applying Deep Learning/03. Traffic Navigation with Deep Reinforcement Learning-az5ElmV4DhY.mp4 40.0 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/21. Mini Project 6 Solution-ji0famK7gOQ.mp4 41.0 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/20. Mini Project 6 Solution-ji0famK7gOQ.mp4 41.0 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/10. DQN Improvements-Zfdbp93A2GU.mp4 41.3 MB
Part 03-Module 01-Lesson 02_Siraj's Stock Prediction/01. How to Predict Stock Prices Easily - Intro to Deep Learning #7-ftMq5ps503w.mp4 41.3 MB
Part 02-Module 05-Lesson 03_Siraj's Image Classification/02. How to Make an Image Classifier - Intro to Deep Learning #6-cAICT4Al5Ow.mp4 42.6 MB
Part 03-Module 02-Lesson 02_Siraj's Style Transfer/01. How to Generate Art - Intro to Deep Learning #8-Oex0eWoU7AQ.mp4 43.2 MB
Part 03-Module 03-Lesson 02_Siraj's Music Generation/01. How to Generate Music - Intro to Deep Learning #9-4DMm5Lhey1U.mp4 45.6 MB
Part 11-Module 01-Lesson 10_Policy-Based Methods/07. M2L3 07 V2-ZBLLGIN1EfU.mp4 45.7 MB
Part 04-Module 01-Lesson 02_Siraj's Video Generation/01. How to Generate Video - Intro to Deep Learning #15--E2N1kQc8MM.mp4 49.1 MB
Part 03-Module 06-Lesson 02_Siraj's Chatbot/01. How to Make a Chatbot - Intro to Deep Learning #12-t5qgjJIBy9g.mp4 49.9 MB
Part 11-Module 01-Lesson 09_Deep Q-Learning/07. Experience Replay-wX_-SZG-YMQ.mp4 50.7 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/13. Understanding Neural Noise-ubqhh4Iv7O4.mp4 52.7 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/14. Understanding Neural Noise-ubqhh4Iv7O4.mp4 52.7 MB
Part 03-Module 08-Lesson 01_Siraj's Image Generation/01. How to Generate Images - Intro to Deep Learning #14-3-UDwk1U77s.mp4 53.2 MB
Part 03-Module 07-Lesson 02_Siraj's Reinforcement Learning/01. How to Win Slot Machines - Intro to Deep Learning #13-AIeWLTUYLZQ.mp4 54.5 MB
Part 07-Module 01-Lesson 04_Sentiment Analysis/13. Mini Project 3 Solution-imnxzCev4SI.mp4 57.2 MB
Part 02-Module 02-Lesson 01_Sentiment Analysis with Andrew Trask/12. Mini Project 3 Solution-imnxzCev4SI.mp4 57.2 MB
Part 01-Module 02-Lesson 01_Regression/03. Siraj's Intro to Deep Learning - How to Make a Prediction-QN1ZwKszguE.mp4 66.5 MB
Part 03-Module 02-Lesson 03_Q&A with FloydHub Founders/01. Floyd QA-KUc59DPfBeo.mp4 226.1 MB

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