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Part 02-Module 01-Lesson 06_Sentiment Analysis/13. Mini Project 3 Solution-imnxzCev4SI.mp4 54.58 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/14. Understanding Neural Noise-ubqhh4Iv7O4.mp4 50.21 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/07. Experience Replay-wX_-SZG-YMQ.mp4 48.38 MB
Part 06-Module 02-Lesson 03_Policy-Based Methods/07. M2L3 07 V2-ZBLLGIN1EfU.mp4 43.55 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/10. DQN Improvements-Zfdbp93A2GU.mp4 39.4 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/21. Mini Project 6 Solution-ji0famK7gOQ.mp4 39.15 MB
Part 01-Module 01-Lesson 03_Applying Deep Learning/03. Traffic Navigation with Deep Reinforcement Learning-az5ElmV4DhY.mp4 38.12 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/10. 12 Backpropagation Example B V6 Final-yiSwuMP2UIA.mp4 37.06 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/25. 23 From RNNs To LSTMs V4 Final-MsqybcWmzGY.mp4 36.16 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/08. 08 Backpropagation Theory V6 Final-Xlgd8I3TWUg.mp4 34.84 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/22. Analysis What's Going on in the Weights-UHsT35pbpcE.mp4 33.67 MB
Part 06-Module 01-Lesson 05_Monte Carlo Methods/03. MC Prediction State Values-0q2wSWyuBj8.mp4 33.39 MB
Part 06-Module 02-Lesson 01_RL in Continuous Spaces/01. Deep Reinforcement Learning-GPjK124RU5g.mp4 33.2 MB
Part 06-Module 02-Lesson 03_Policy-Based Methods/02. M2L3 02 V2-ToS8vXGdODE.mp4 32.51 MB
Part 06-Module 01-Lesson 04_Dynamic Programming/14. Policy Improvement-4_adUEK0IHg.mp4 30.38 MB
Part 06-Module 01-Lesson 06_Temporal-Difference Methods/03. TD Prediction TD(0)-CsD6b0csU7o.mp4 30.11 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/18. Mini Project 5 Solution-Hv86B_jjWTI.mp4 28.86 MB
Part 06-Module 02-Lesson 01_RL in Continuous Spaces/11. Linear Function Approximation-OJ5wrB7o-pI.mp4 28.67 MB
Part 06-Module 01-Lesson 04_Dynamic Programming/05. An Iterative Method-AX-hG3KvwzY.mp4 27.57 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/06. 07 FeedForward B V3-kTYbTVh1d0k.mp4 26.65 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/05. 04 RNN FFNN Reminder A V7 Final-_vrp2lZjXf0.mp4 25.79 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/06. Deep Q Network-GgtR_d1OB-M.mp4 25.67 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/07. Mini Project 1 Solution-l4r5l0HvHRI.mp4 24.79 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/03. 02 RNN History V4 Final-HbxAnYUfRnc.mp4 24.26 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/02. Andrew Trask - Intro-da1I0mea1jQ.mp4 23.76 MB
Part 04-Module 01-Lesson 05_Embeddings and Word2vec/02. Implementing Word2Vec-7M431_f9HgE.mp4 23.33 MB
Part 04-Module 01-Lesson 06_Sentiment Prediction RNN/07. Sentiment RNN 2-V9YGGjmoHS0.mp4 23.11 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/19. Further Noise Reduction-Kl3hWxizKVg.mp4 22.33 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/16. 18 RNN Example V5 Final-MDLk3fhpTx0.mp4 22.11 MB
Part 06-Module 01-Lesson 05_Monte Carlo Methods/06. MC Prediction Action Values-08tLtbh0xLs.mp4 22.01 MB
Part 06-Module 01-Lesson 05_Monte Carlo Methods/13. MC Control Policy Improvement-2RKH-BInX7s.mp4 22 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/17. 19 RNN BPTT A V6 Final-eE2L3-2wKac.mp4 21.57 MB
Part 03-Module 01-Lesson 05_Autoencoders/05. Convolutional Autoencoders-18SZVRaumGs.mp4 21.51 MB
Part 06-Module 02-Lesson 01_RL in Continuous Spaces/03. Discrete vs. Continuous Spaces-uHstLeRzaE8.mp4 21.37 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/13. 16 RNN B V4 Final-wsif3p5t7CI.mp4 21.12 MB
Part 06-Module 02-Lesson 03_Policy-Based Methods/04. M2L3 04 V1-QicxmyE5vTo.mp4 21.03 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/08. Fixed Q Targets-SWpyiEezfp4.mp4 20.97 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/02. 01 RNN Intro V6 Final-AIQEqg6F38A.mp4 20.89 MB
Part 06-Module 01-Lesson 06_Temporal-Difference Methods/01. Introduction-yXErXQulI_o.mp4 20.67 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/16. Understanding Inefficiencies in our Network-4MuS-6ATxCU.mp4 20.67 MB
Part 06-Module 01-Lesson 03_The RL Framework The Solution/02. Policies-hc3LrvaC13U.mp4 20.24 MB
Part 06-Module 02-Lesson 01_RL in Continuous Spaces/10. Function Approximation-UTGWVY6jEdg.mp4 20.08 MB
Part 06-Module 01-Lesson 05_Monte Carlo Methods/10. MC Control Incremental Mean-E2RITH-2NUE.mp4 20.07 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/05. 05 RNN FFNN Reminder B V6 Final-FfPjaGcZODc.mp4 19.68 MB
Part 04-Module 01-Lesson 06_Sentiment Prediction RNN/05. Building The RNN 1-XTD6slf64fM.mp4 19.11 MB
Part 06-Module 02-Lesson 03_Policy-Based Methods/03. M2L3 03 V2-TePX-0Bs23E.mp4 18.85 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/17. CNNs For Image Classification-l9vg_1YUlzg.mp4 18.16 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/18. 20 RNN BPTT B V5 Final-bUU9BEQw0IA.mp4 18.1 MB
Part 05-Module 01-Lesson 04_Semi-Supervised Learning/05. Building The Generator And Discriminator-OWytckbbeGQ.mp4 17.97 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/06. 06 FeedForward A V7 Final-4rCfnWbx8-0.mp4 17.74 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/02. Aplicações de CNNs-HrYNL_1SV2Y.mp4 17.7 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/05. Framing the Problem-IsTOnkAKaJw.mp4 17.65 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/09. Deep Q-Learning Algorithm-MqTXoCxQ_eY.mp4 17.45 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/05. Q-Learning-AI5gLgYMSq8.mp4 17.31 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/04. 03 RNN Applications V3 Final-6JbTNARuKII.mp4 17.27 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/19. 21 RNN BPTT C V7 Final-uBy_eIJDD1M.mp4 17.23 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/11. Camadas convolucionais-RnM1D-XI--8.mp4 17.05 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/04. Temporal Difference Learning-lpmDi0QeUm8.mp4 16.98 MB
Part 06-Module 02-Lesson 04_Actor-Critic Methods/07. Summary-hvYQ_3LgCYs.mp4 16.9 MB
Part 06-Module 02-Lesson 03_Policy-Based Methods/05. M2L3 05 V1-eZxxNNIZuwA.mp4 16.64 MB
Part 06-Module 01-Lesson 06_Temporal-Difference Methods/10. TD Control Sarsamax-4DxoYuR7aZ4.mp4 16.53 MB
Part 05-Module 01-Lesson 02_Deep Convolutional GANs/05. DCGAN And The Generator-CH6BxLTKt7s.mp4 16.03 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/05. GANs Architecture -gaEs7ccZv_Q.mp4 15.96 MB
Part 05-Module 01-Lesson 04_Semi-Supervised Learning/06. Model Loss Exercise-W7TawMNxBds.mp4 15.85 MB
Part 03-Module 01-Lesson 05_Autoencoders/03. A-Simple-Autoencoders 21718-lXGdkCT8E1c.mp4 15.66 MB
Part 06-Module 01-Lesson 04_Dynamic Programming/23. Value Iteration-XNeQn8N36y8.mp4 15.65 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/09. 10 Backpropagation Example A V3 Final-3k72z_WaeXg.mp4 14.77 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/17. MDPs, Part 3-UlXHFbla3QI.mp4 14.75 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/11. Discounted Return-opXGNPwwn7g.mp4 14.3 MB
Part 06-Module 01-Lesson 04_Dynamic Programming/20. Truncated Policy Iteration-a-RvCxlPMho.mp4 14.13 MB
Part 04-Module 01-Lesson 03_Implementation of RNN and LSTM/05. Implementing a Character-wise RNN-KPCMn_jg2oY.mp4 13.63 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/04. Games, Equilibrium, GANs Solution Render-2zi8DOWIVas.mp4 13.4 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/25. Transfer Learning-LHG5FltaR6I.mp4 13.32 MB
Part 04-Module 01-Lesson 03_Implementation of RNN and LSTM/13. Build The Network And Results-hu8iMMqajmQ.mp4 13.27 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/26. Transfer Learning in Keras-HsIAznMM1LA.mp4 12.92 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/08. 13 Overfitting Intro V4 Final-rmBLnVbFfFY.mp4 12.76 MB
Part 03-Module 01-Lesson 05_Autoencoders/06. Convolutional Autoencoder Solutions-w3iPs6YnqmY.mp4 12.68 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/02. Neural Nets as Value Functions-cBi7vLrk8QQ.mp4 12.65 MB
Part 05-Module 01-Lesson 04_Semi-Supervised Learning/07. Model Optimization Exercise-wNpI1wUA4Io.mp4 12.64 MB
Part 06-Module 02-Lesson 01_RL in Continuous Spaces/05. Discretization-j2eZyUpy--E.mp4 12.55 MB
Part 06-Module 01-Lesson 05_Monte Carlo Methods/18. MC Control Constant-alpha-QFV1nI9Zpoo.mp4 12.46 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/09. Local Connectivity-z9wiDg0w-Dc.mp4 12.02 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/02. Cool Things To Do With GANs-bo-ToTdhgew.mp4 11.98 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/23. Andrew Trask - Outro-nIF0GLOQglQ.mp4 11.79 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/16. A Trained GAN-TR-uEJcjig4.mp4 11.67 MB
Part 01-Module 01-Lesson 01_Welcome to Deep Learning/01. 01 Welcome To The Deep Learning Program-3QPEmwq2NaE.mp4 11.28 MB
Part 02-Module 01-Lesson 02_Implementing Gradient Descent/03. Gradient Descent-Math-7sxA5Ap8AWM.mp4 11.25 MB
Part 01-Module 01-Lesson 01_Welcome to Deep Learning/02. Meet Your Instructors--UOFRxCu414.mp4 11.25 MB
Part 04-Module 01-Lesson 06_Sentiment Prediction RNN/02. Sentiment Prediction-uGN3rZJRiMY.mp4 11.25 MB
Part 03-Module 01-Lesson 04_Weight Initialization/03. Weight Initialization 2-BI3f0Cdc_nU.mp4 11.1 MB
Part 01-Module 01-Lesson 01_Welcome to Deep Learning/05. Projects You will Build-PqpdX7YxTlU.mp4 11.05 MB
Part 06-Module 02-Lesson 01_RL in Continuous Spaces/07. Tile Coding-BRs7AnTZ_8k.mp4 11.03 MB
Part 03-Module 01-Lesson 04_Weight Initialization/02. Weight Initialization 1-6vXMYu_TQIA.mp4 10.75 MB
Part 06-Module 02-Lesson 04_Actor-Critic Methods/05. RL M2L4 05 Advantage Function RENDER V1 V2-vpLmzKqcgfc.mp4 10.72 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/01. 00 Luis Introducing Ortal Newtitle121217-oXv7GiC-jrM.mp4 10.69 MB
Part 01-Module 01-Lesson 05_Matrix Math and NumPy Refresher/02. Data Has Dimensions-F4NSv776X0c.mp4 10.61 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/14. 17 RNN Unfolded V3 Final-xLIA_PTWXog.mp4 10.5 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/12. 14 RNN A V4 Final-ofbnDxGSUcg.mp4 10.43 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/03. Monte Carlo Learning-qOviWYwcvsg.mp4 10.41 MB
Part 06-Module 02-Lesson 04_Actor-Critic Methods/01. RL M2L4 01 Actor Critic Methods RENDER V1 V1-FXhyxJzgt8U.mp4 10.38 MB
Part 06-Module 02-Lesson 01_RL in Continuous Spaces/09. Coarse Coding-Uu1J5KLAfTU.mp4 10.3 MB
Part 01-Module 01-Lesson 02_Anaconda/02. Why Anaconda-VXukXZv7SCQ.mp4 10.29 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/03. Other Generative Models, How GANs Work-MF0QCP1OC9I.mp4 10.28 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/20. Image Augmentation in Keras-odStujZq3GY.mp4 10.26 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/11. Building a Neural Network-aM2k7RTjjJI.mp4 10.17 MB
Part 05-Module 01-Lesson 04_Semi-Supervised Learning/02. Semi-Supervised Learning-_LRpHPxZaX0.mp4 10.11 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/03. Episodic vs. Continuing Tasks-E1I-BPanSM8.mp4 10.07 MB
Part 06-Module 02-Lesson 04_Actor-Critic Methods/04. RL M2L4 04 The Actor And The Critic V1-bvbE9F7urd4.mp4 10.01 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/10. Cumulative Reward-ysriH65lV9o.mp4 9.96 MB
Part 06-Module 02-Lesson 01_RL in Continuous Spaces/14. Summary-MTEBk43oByU.mp4 9.91 MB
Part 04-Module 01-Lesson 05_Embeddings and Word2vec/09. Training Results-uISA5ns47s8.mp4 9.78 MB
Part 06-Module 01-Lesson 06_Temporal-Difference Methods/06. TD Prediction Action Values-1c029-7_9GA.mp4 9.73 MB
Part 04-Module 01-Lesson 05_Embeddings and Word2vec/03. Subsampling Solution-MAUM_mV_lj8.mp4 9.65 MB
Part 04-Module 01-Lesson 04_Hyperparameters/03. Learning Rate-HLMjeDez7ps.mp4 9.62 MB
Part 03-Module 01-Lesson 04_Weight Initialization/05. Weight Initialization 4-FM6t7AsodGQ.mp4 9.56 MB
Part 06-Module 01-Lesson 01_Introduction to RL/04. OpenAI Gym-MktEOWp3QLg.mp4 9.47 MB
Part 03-Module 01-Lesson 06_Transfer Learning in TensorFlow/05. Data Preparation-WfsDMq-b3y4.mp4 9.23 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/10. Mini Project 2 Solution-45ihpPaeO8E.mp4 9.22 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/23. Visualizando CNNs-mnqS_EhEZVg.mp4 9.2 MB
Part 06-Module 01-Lesson 05_Monte Carlo Methods/12. MC Control Policy Evaluation-3_opwMzpEEI.mp4 9.1 MB
Part 01-Module 01-Lesson 05_Matrix Math and NumPy Refresher/09. Matrix Transposes-NVK5xCY3CZE.mp4 9.09 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/01. Intro to Deep Q-Learning-o3cmuUDhP3I.mp4 9.08 MB
Part 04-Module 01-Lesson 03_Implementation of RNN and LSTM/09. RNN Output-RkanDkcrTxs.mp4 8.92 MB
Part 06-Module 02-Lesson 01_RL in Continuous Spaces/12. Kernel Functions-RdkPVYyVOvU.mp4 8.91 MB
Part 03-Module 01-Lesson 06_Transfer Learning in TensorFlow/03. Building VGGNet-615SslQiGvo.mp4 8.87 MB
Part 05-Module 01-Lesson 04_Semi-Supervised Learning/10. Model Loss Solution-r3DtohmychE.mp4 8.84 MB
Part 08-Module 01-Lesson 02_Regression/22. Regularization-PyFNIcsNma0.mp4 8.76 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/18. CNNs in Keras Practical Example-faFvmGDwXX0.mp4 8.71 MB
Part 06-Module 02-Lesson 04_Actor-Critic Methods/02. RL M2L4 02 A Better Score Function V2-_HBJ3l10-OE.mp4 8.68 MB
Part 03-Module 01-Lesson 05_Autoencoders/04. Simple Autoencoder Solution-Nv_D6DHfEk8.mp4 8.59 MB
Part 06-Module 01-Lesson 01_Introduction to RL/02. Applications-CV6B84mKRNM.mp4 8.46 MB
Part 06-Module 01-Lesson 04_Dynamic Programming/08. M1 L1 C05 V3 No Slack-OH-fVUpoyZDyGE.mp4 8.43 MB
Part 04-Module 01-Lesson 06_Sentiment Prediction RNN/06. Training The Network-nknJ3Xu3ld0.mp4 8.41 MB
Part 03-Module 01-Lesson 06_Transfer Learning in TensorFlow/02. Transfer Learning--WmQwYr0DYjY.mp4 8.28 MB
Part 05-Module 01-Lesson 02_Deep Convolutional GANs/02. Deconvolution-sX_AxtB6CHI.mp4 8.27 MB
Part 03-Module 01-Lesson 06_Transfer Learning in TensorFlow/10. Training And Testing-NLPtmQjGYCA.mp4 8.23 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/26. Conclusion-WhpE_8sTt-0.mp4 8.2 MB
Part 06-Module 01-Lesson 04_Dynamic Programming/17. Policy Iteration-gqv7o1kBDc0.mp4 8.14 MB
Part 04-Module 01-Lesson 05_Embeddings and Word2vec/06. Building The Network-fhSb5c6UX6M.mp4 8.09 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/22. Groundbreaking CNN Architectures-ddrB-mhMfkY.mp4 8.09 MB
Part 05-Module 01-Lesson 02_Deep Convolutional GANs/09. Building And Training The Network-nXKk9GI4X14.mp4 8.08 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/08. Goals and Rewards, Part 2-pVIFc72VYH8.mp4 8.05 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/10. Convolutional Layers-h5R_JvdUrUI.mp4 8.04 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/12. Stride and Padding-0r9o8hprDXQ.mp4 7.98 MB
Part 04-Module 01-Lesson 03_Implementation of RNN and LSTM/07. LSTM Cell-ajC-5uWB8S4.mp4 7.79 MB
Part 01-Module 01-Lesson 01_Welcome to Deep Learning/10. Getting-Setup-1SuxTnuQkeE.mp4 7.76 MB
Part 06-Module 01-Lesson 01_Introduction to RL/03. The Setting-nh8Gwdu19nc.mp4 7.75 MB
Part 04-Module 01-Lesson 05_Embeddings and Word2vec/04. Making Batches-jx7qwdw-94k.mp4 7.73 MB
Part 06-Module 02-Lesson 03_Policy-Based Methods/08. M2L3 08 V1-og3W6CXn1F0.mp4 7.63 MB
Part 06-Module 01-Lesson 06_Temporal-Difference Methods/07. TD Control Sarsa(0)-LkFkjfsRpXc.mp4 7.63 MB
Part 02-Module 01-Lesson 03_Training Neural Networks/07. Regularization-ndYnUrx8xvs.mp4 7.57 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/img/chess-game.jpg 7.54 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/02. Introduction-tn-CrUTkCUc.mp4 7.54 MB
Part 05-Module 01-Lesson 04_Semi-Supervised Learning/09. Discriminator Solution-_X8ssUzu_Bo.mp4 7.43 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/02. The Setting, Revisited-V6Q1uF8a6kA.mp4 7.36 MB
Part 01-Module 01-Lesson 05_Matrix Math and NumPy Refresher/07. Matrix Multiplication Part 2-8jtk8BzBdj8.mp4 7.34 MB
Part 04-Module 01-Lesson 05_Embeddings and Word2vec/08. Building The Network Solution-pkBAhQ2Ki-8.mp4 7.34 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/24. RNN Summary-nXP0oGGRrO8.mp4 7.26 MB
Part 05-Module 01-Lesson 02_Deep Convolutional GANs/06. Generator Solution-jyPwUEZg05Q.mp4 7.26 MB
Part 08-Module 02-Lesson 01_MiniFlow/01. Miniflow Introduction-Nqp_UifEwt0.mp4 7.22 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/14. Error Functions-jfKShxGAbok.mp4 7.21 MB
Part 06-Module 02-Lesson 02_Deep Q-Learning/13. Wrap Up-x6JggcDTcys.mp4 7.2 MB
Part 05-Module 01-Lesson 04_Semi-Supervised Learning/12. Trained Semi-Supervised GAN-9yWYZDX8-O8.mp4 7.2 MB
Part 01-Module 01-Lesson 04_Jupyter Notebooks/02. Jupyter-qiYDWFLyXvg.mp4 7.12 MB
Part 06-Module 01-Lesson 03_The RL Framework The Solution/11. Optimal Policies-2rguYpVyCto.mp4 7.11 MB
Part 04-Module 01-Lesson 03_Implementation of RNN and LSTM/12. Build The Network-RVNjDlWTBQU.mp4 7.1 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/08. Generator Network-btHVXnICmzQ.mp4 7.08 MB
Part 05-Module 01-Lesson 02_Deep Convolutional GANs/10. Hyperparameters Solution-Rt8MlVDtpi8.mp4 7 MB
Part 06-Module 01-Lesson 01_Introduction to RL/05. Resources-_YPqfAnCqtk.mp4 6.97 MB
Part 06-Module 01-Lesson 05_Monte Carlo Methods/09. Generalized Policy Iteration-XRmz4nolEsw.mp4 6.92 MB
Part 04-Module 01-Lesson 06_Sentiment Prediction RNN/03. Data Preprocessing-h4-LwZU9_k8.mp4 6.86 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/07. Goals and Rewards, Part 1-XPnj3Ya3EuM.mp4 6.84 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/15. Training Losses and Optimizers Solutions-HlABZ9Q7xEo.mp4 6.82 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/14. MDPs, Part 2-CUTtQvxKkNw.mp4 6.82 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/18. ROC Curve-2Iw5TiGzJI4.mp4 6.66 MB
Part 08-Module 01-Lesson 01_Evaluation Metrics/11. ROC Curve-2Iw5TiGzJI4.mp4 6.66 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/08. Transforming Text into Numbers-7rHBU5cbePE.mp4 6.64 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/21. CrossEntropy V1-1BnhC6e0TFw.mp4 6.61 MB
Part 06-Module 01-Lesson 03_The RL Framework The Solution/09. Action-Value Functions-KJLaRfOOPGA.mp4 6.6 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/34. Backpropagation V2-1SmY3TZTyUk.mp4 6.52 MB
Part 02-Module 01-Lesson 03_Training Neural Networks/04. Underfitting And Overfitting-xj4PlXMsN-Y.mp4 6.42 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/10. Generator and Discriminator Solutions-9By2pAck044.mp4 6.29 MB
Part 02-Module 01-Lesson 05_Project Predicting Bike Sharing Data/01. Introduction to the Project-dOwEDeJp8yw.mp4 6.23 MB
Part 06-Module 01-Lesson 04_Dynamic Programming/01. Introduction-ek2PD9RDrWw.mp4 6.18 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/03. How Computers Interpret Images-V4f6p6uRhu8.mp4 6.18 MB
Part 05-Module 01-Lesson 04_Semi-Supervised Learning/04. Data Prep-P5hOx09mwaM.mp4 6.15 MB
Part 06-Module 02-Lesson 04_Actor-Critic Methods/03. RL M2L4 03 Two Function Approximators V1-37KQEgLaLfw.mp4 6.13 MB
Part 06-Module 01-Lesson 03_The RL Framework The Solution/01. M0 L3 C01 Intro- V3 No Slack-OH-5IlSH-eoPAU.mp4 6.09 MB
Part 06-Module 01-Lesson 03_The RL Framework The Solution/08. Optimality-j231aRV74QM.mp4 5.99 MB
Part 01-Module 01-Lesson 05_Matrix Math and NumPy Refresher/06. Matrix Multiplication Part 1-JRoCFQRP4B0.mp4 5.89 MB
Part 05-Module 01-Lesson 04_Semi-Supervised Learning/03. Introducing Semi-Supervised Learning-tnCClNy5z5c.mp4 5.88 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/13. Training Losses-IaAeDrXMEcU.mp4 5.83 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/15. Pooling Layers-OkkIZNs7Cyc.mp4 5.82 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/18. Maximum Likelihood 1-1yJx-QtlvNI.mp4 5.75 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/34. DL 46 Calculating The Gradient 2 V2 (2)-7lidiTGIlN4.mp4 5.69 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/07. When do MLPs (not) work well-deMeuLdZN3Q.mp4 5.54 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/12. Validating The Training-Oxm9ofvov3I.mp4 5.51 MB
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Part 03-Module 01-Lesson 04_Weight Initialization/04. Weight Initialization 3-JIQl0jMpdsI.mp4 5.43 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/05. Categorical Cross-Entropy-3sDYifgjFck.mp4 5.42 MB
Part 07-Module 01-Lesson 01_Enroll in your next Nanodegree program/img/carnd.jpg 5.35 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/15. Discrete vs. Continuous-Rm2KxFaPiJg.mp4 5.35 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/33. DL 41 Feedforward FIX V2-hVCuvMGOfyY.mp4 5.33 MB
Part 06-Module 01-Lesson 03_The RL Framework The Solution/05. State-Value Functions-llakAjwox_8.mp4 5.28 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/06. Model Validation in Keras-002jNXSM6CU.mp4 5.2 MB
Part 08-Module 01-Lesson 02_Regression/06. Absolute Trick-DJWjBAqSkZw.mp4 5.17 MB
Part 06-Module 01-Lesson 01_Introduction to RL/01. Introduction-6jSFl5kxIBs.mp4 5.15 MB
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Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/24. Confusion Matrix-Question 1-9GLNjmMUB_4.mp4 5.04 MB
Part 08-Module 01-Lesson 01_Evaluation Metrics/02. Confusion Matrix-Question 1-9GLNjmMUB_4.mp4 5.04 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/07. Getting Started with GANs-QA2ntKUha4g.mp4 5.04 MB
Part 06-Module 02-Lesson 03_Policy-Based Methods/01. M2L3 01 V1-YOSREyp04HA.mp4 4.98 MB
Part 06-Module 02-Lesson 01_RL in Continuous Spaces/13. Non-Linear Function Approximation-rITnmpD2mN8.mp4 4.95 MB
Part 06-Module 01-Lesson 05_Monte Carlo Methods/01. Introduction-W2EP3riQSus.mp4 4.93 MB
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Part 02-Module 01-Lesson 01_Introduction to Neural Networks/23. Error Function-V5kkHldUlVU.mp4 4.84 MB
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Part 02-Module 01-Lesson 01_Introduction to Neural Networks/32. Combinando modelos-Boy3zHVrWB4.mp4 4.73 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/02. 02 Skin Cancer V4-70jGZeiTNgk.mp4 4.73 MB
Part 04-Module 01-Lesson 03_Implementation of RNN and LSTM/11. Output And Loss Solutions-CT8hcU7FmGc.mp4 4.69 MB
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Part 03-Module 01-Lesson 06_Transfer Learning in TensorFlow/06. Data Preparation-WEtKkHlhhZA.mp4 4.4 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/04. MLPs For Image Classification-TIFStebu530.mp4 4.4 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/06. The Reward Hypothesis-uAqNwgZ49JE.mp4 4.38 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/12. Building the Network Solution-Ikp3rVzG970.mp4 4.33 MB
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Part 02-Module 01-Lesson 01_Introduction to Neural Networks/20. Cross Entropy 1-iREoPUrpXvE.mp4 4.22 MB
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Part 03-Module 01-Lesson 06_Transfer Learning in TensorFlow/09. Training The Classifier-b7Fy3cIoJ1Y.mp4 4.19 MB
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Part 04-Module 01-Lesson 04_Hyperparameters/08. RNN Hyperparameters-yQvnv7l_aUo.mp4 4.12 MB
Part 02-Module 01-Lesson 06_Sentiment Analysis/01. Introducing Andrew Trask-ltO71Bm8b3M.mp4 4.08 MB
Part 01-Module 01-Lesson 05_Matrix Math and NumPy Refresher/04. Element-wise Matrix Operations-vjUykZyzko4.mp4 4.03 MB
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Part 02-Module 01-Lesson 01_Introduction to Neural Networks/16. DL 18 Q Softmax V2-RC_A9Tu99y4.mp4 4.01 MB
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Part 05-Module 01-Lesson 02_Deep Convolutional GANs/08. Discriminator Solution-ffPWI2yJscw.mp4 3.87 MB
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Part 08-Module 01-Lesson 02_Regression/11. Minimizing Error Functions-RbT2TXN_6tY.mp4 3.85 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/05. Linear Boundaries-X-uMlsBi07k.mp4 3.85 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/18. Maximum Likelihood 2-6nUUeQ9AeUA.mp4 3.85 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/24. Gradient Descent-rhVIF-nigrY.mp4 3.76 MB
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Part 02-Module 01-Lesson 01_Introduction to Neural Networks/13. Error Functions-YfUUunxWIJw.mp4 3.54 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.09.24-pm.png 3.49 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/23. What Is The Neural Network Looking At-qN-rvoxPbBw.mp4 3.46 MB
Part 08-Module 01-Lesson 02_Regression/23. Neural Network Regression-aUJCBqBfEnI.mp4 3.46 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/14. Training Optimizers-AU5gH7LS57E.mp4 3.45 MB
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Part 02-Module 01-Lesson 01_Introduction to Neural Networks/32. Layers-pg99FkXYK0M.mp4 3.11 MB
Part 06-Module 02-Lesson 04_Actor-Critic Methods/06. RL M2L4 06 Actor Critic With Advantage RENDER V1 V1-Bwd2OF7hJXQ.mp4 3.09 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.09.02-pm.png 3.09 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/25. Confusion Matrix-3rpN-YYlfes.mp4 3.07 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/19. Quiz - Cross 1--xxrisIvD0E.mp4 3.02 MB
Part 06-Module 02-Lesson 03_Policy-Based Methods/06. M2L3 06 V1-RMjdQkl6CqE.mp4 3.01 MB
Part 02-Module 01-Lesson 03_Training Neural Networks/02. Training Optimization-UiGKhx9pUYc.mp4 2.96 MB
Part 06-Module 01-Lesson 02_The RL Framework The Problem/01. Introduction-X_9l_ZqXXBA.mp4 2.9 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.08.11-pm.png 2.9 MB
Part 04-Module 01-Lesson 03_Implementation of RNN and LSTM/02. Character-Wise RNN-dXl3eWCGLdU.mp4 2.88 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/11. Perceptron Agorithm Pseudocode-p8Q3yu9YqYk.mp4 2.87 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/05. The Data-2RLbbV7MQNA.mp4 2.85 MB
Part 02-Module 01-Lesson 02_Implementing Gradient Descent/06. Multilayer perceptrons-Rs9petvTBLk.mp4 2.85 MB
Part 08-Module 01-Lesson 02_Regression/18. Closed Form Solution-G3fRVgLa5gI.mp4 2.84 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/11. Solution Random Vs Preinitialized Thoughts-sOuoRZRKDzs.mp4 2.83 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/32. 29 Neural Network Architecture 2-FWN3Sw5fFoM.mp4 2.83 MB
Part 06-Module 01-Lesson 07_Solve OpenAI Gym's Taxi-v2 Task/img/open-agent-monitor-main.gif 2.73 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/09. DL 08 AND And OR Perceptrons-Y-ImuxNpS40.mp4 2.73 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/21. ROC Curve-fWwe_JlpnlQ.mp4 2.68 MB
Part 08-Module 01-Lesson 02_Regression/16. Higher Dimensions--UvpQV1qmiE.mp4 2.65 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/06. 09 Higher Dimensions-eBHunImDmWw.mp4 2.59 MB
Part 02-Module 01-Lesson 08_TensorFlow/17. Conclusion-wOiUQDgGD9E.mp4 2.58 MB
Part 08-Module 01-Lesson 02_Regression/09. Mean Absolute Error-vLKiY0Ehors.mp4 2.57 MB
Part 02-Module 01-Lesson 02_Implementing Gradient Descent/02. Gradient Descent-29PmNG7fuuM.mp4 2.46 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/img/screen-shot-2017-10-27-at-1.29.13-pm.png 2.45 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/22. Visualization-aGIGB4Ta3_A.mp4 2.43 MB
Part 06-Module 01-Lesson 03_The RL Framework The Solution/04. Gridworld Example-XeHBmPFqTsE.mp4 2.38 MB
Part 08-Module 01-Lesson 01_Evaluation Metrics/04. Accuracy-s6SfhPTNOHA.mp4 2.34 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/17. 16 Solution Diagnosing Cancer V3-IJYvt2ssUFk.mp4 2.31 MB
Part 02-Module 01-Lesson 03_Training Neural Networks/12. Other Activation Functions-kA-1vUt6cvQ.mp4 2.3 MB
Part 04-Module 01-Lesson 03_Implementation of RNN and LSTM/03. Sequence-Batching-Z4OiyU0Cldg.mp4 2.29 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.mp4 2.26 MB
Part 08-Module 01-Lesson 01_Evaluation Metrics/09. 06 Precision SC V1-q2wVorBfefU.mp4 2.24 MB
Part 08-Module 01-Lesson 01_Evaluation Metrics/08. Answer False Negatives And Positives-KOytJL1lvgg.mp4 2.23 MB
Part 03-Module 01-Lesson 05_Autoencoders/02. Autoencoders-ar5Iyx68cWc.mp4 2.22 MB
Part 04-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/05. Learn Gate-aVHVI7ovbHY.mp4 2.22 MB
Part 04-Module 01-Lesson 04_Hyperparameters/02. Introduction-erwnzFD7AeE.mp4 2.22 MB
Part 08-Module 01-Lesson 01_Evaluation Metrics/07. 04 Quiz False Negatives And Positives SC V1-_ytP9zIkziw.mp4 2.22 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/04. Medical Classification-RCOSP60dV7U.mp4 2.2 MB
Part 05-Module 01-Lesson 03_Generate Faces/01. Last Project - Congrats-UUqU8SYBZ9Q.mp4 2.2 MB
Part 02-Module 01-Lesson 07_Keras/06. Keras Lab-a50un22BsLI.mp4 2.19 MB
Part 08-Module 01-Lesson 01_Evaluation Metrics/06. When Accuracy Wont Work-r0-O-gIDXZ0.mp4 2.15 MB
Part 08-Module 01-Lesson 01_Evaluation Metrics/10. 07 Recall SC V1-0n5wUZiefkQ.mp4 2.15 MB
Part 02-Module 01-Lesson 03_Training Neural Networks/15. Momentum-r-rYz_PEWC8.mp4 2.14 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/30. Non-Linear Data-F7ZiE8PQiSc.mp4 2.14 MB
Part 04-Module 01-Lesson 06_Sentiment Prediction RNN/04. Creating Testing Sets-BRBbrNLz1ho.mp4 2.13 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/21. Formula For Cross 1-qvr_ego_d6w.mp4 2.08 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/03. Exemplo de classificação-Dh625piH7Z0.mp4 2.07 MB
Part 03-Module 01-Lesson 02_Convolutional Neural Networks/01. Apresentando Alexis-38ExGpdyvJI.mp4 2.05 MB
Part 02-Module 01-Lesson 03_Training Neural Networks/03. Testing-EeBZpb-PSac.mp4 2 MB
Part 03-Module 01-Lesson 06_Transfer Learning in TensorFlow/07. Building The Classifier-pPHiVddBY0Q.mp4 1.99 MB
Part 06-Module 01-Lesson 07_Solve OpenAI Gym's Taxi-v2 Task/img/run-main.gif 1.99 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/25. Gradient Descent Algorithm-snxmBgi_GeU.mp4 1.98 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/16. DL 18 S Softmax-n8S-v_LCTms.mp4 1.95 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/10. Perceptron Algorithm--zhTROHtscQ.mp4 1.92 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/32. Multiclass Classification-uNTtvxwfox0.mp4 1.88 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/19. Quiz Cross Entropy-njq6bYrPqSU.mp4 1.86 MB
Part 08-Module 01-Lesson 02_Regression/10. Mean Squared Error-MRyxmZDngI4.mp4 1.83 MB
Part 02-Module 01-Lesson 03_Training Neural Networks/16. Error Functions Around the World-34AAcTECu2A.mp4 1.73 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.mp4 1.73 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/33. DL 42 Neural Network Error Function (1)-SC1wEW7TtKs.mp4 1.72 MB
Part 04-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/11. Other Architectures-MsxFDuYlTuQ.mp4 1.71 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/17. One-Hot Encoding-AePvjhyvsBo.mp4 1.65 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/img/skin-disease-classes.png 1.64 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/04. 分类问题 2 -46PywnGa_cQ.mp4 1.62 MB
Part 05-Module 01-Lesson 03_Generate Faces/02. 项目简介-jvJtHYBX7sM.mp4 1.61 MB
Part 04-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/09. Putting It All Together-IF8FlKW-Zo0.mp4 1.58 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/10. 10 Quiz Random Vs Preinitiliazed Weights V3-DRC1e4XGl2M.mp4 1.58 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/14. Solution Sensitivty And Specificity-GBZjyeMjKxc.mp4 1.57 MB
Part 08-Module 01-Lesson 02_Regression/25. Conclusion-pyeojf0NniQ.mp4 1.57 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/img/lesions.png 1.57 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/01. Introduction-ZCpXvVdIdnY.mp4 1.55 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/03. Survival Rate-QPlp3NeGuSk.mp4 1.52 MB
Part 04-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/08. LSTM 7 Use Gate-5Ifolm1jTdY.mp4 1.5 MB
Part 06-Module 01-Lesson 04_Dynamic Programming/img/frozen-lake-6.jpg 1.5 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/23. DL 29 Logistic Regression-Minimizing The Error Function-KayqiYijlzc.mp4 1.49 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/08. Solution Data Challenges-1z3o4niQuNg.mp4 1.49 MB
Part 08-Module 01-Lesson 02_Regression/02. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.mp4 1.48 MB
Part 04-Module 01-Lesson 04_Hyperparameters/06. Number Of Iterations-TTdHpSb4DV8.mp4 1.46 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/06. 06 Image Challenge V3-Efnoj1KNPHw.mp4 1.46 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/34. Chain Rule-YAhIBOnbt54.mp4 1.46 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/09. Regra da cadeia-YAhIBOnbt54.mp4 1.46 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/12. Non-Linear Regions-B8UrWnHh1Wc.mp4 1.33 MB
Part 02-Module 01-Lesson 03_Training Neural Networks/11. Vanishing Gradient-W_JJm_5syFw.mp4 1.32 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/09. Training The Neural Network-HwiI-UXUx-M.mp4 1.24 MB
Part 08-Module 02-Lesson 01_MiniFlow/07. Pixels are Features!-qE5YYXtPq9U.mp4 1.24 MB
Part 03-Module 01-Lesson 03_CNNs in TensorFlow/img/arch.png 1.2 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/28. Mini Project Introduction-Rgf3YVFWl-M.mp4 1.15 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.mp4 1.14 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/29. Continuous Perceptrons-07-JJ-aGEfM.mp4 1.13 MB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/31. Non-Linear Models-HWuBKCZsCo8.mp4 1.13 MB
Part 08-Module 01-Lesson 02_Regression/04. Fitting A Line-gkdoknEEcaI.mp4 1.12 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/img/screen-shot-2017-12-04-at-12.31.11-pm.png 1.12 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/20. Solution ROC Curve-sdUUf6RRmXI.mp4 1.11 MB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/19. 17 Quiz ROC Curve 1 PT2 V1-Xv3v59_CfEU.mp4 1.11 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/img/screen-shot-2017-10-11-at-2.04.14-pm.png 1.1 MB
Part 08-Module 01-Lesson 01_Evaluation Metrics/03. Confusion-Matrix-Solution-ywwSzyU9rYs.mp4 1.1 MB
Part 04-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/04. LSTM Architecture-ycwthhdx8ws.mp4 1.07 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/img/screen-shot-2017-12-03-at-10.43.49-pm.png 1.05 MB
Part 05-Module 01-Lesson 01_Generative Adversarial Networks/09. Discriminator Network-nWXxT8OqCfs.mp4 1.04 MB
Part 04-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/06. Forget Gate-iWxpfxLUPSU.mp4 1.04 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/img/screen-shot-2017-12-04-at-11.12.31-am.png 1.03 MB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/img/screen-shot-2017-12-04-at-11.16.19-am.png 1.02 MB
Part 02-Module 01-Lesson 03_Training Neural Networks/06. DL 53 Q Regularization-KxROxcRsHL8.mp4 1.01 MB
Part 08-Module 01-Lesson 02_Regression/03. Solution Housing Prices-uhdTulw9-Nc.mp4 1001.4 KB
Part 06-Module 01-Lesson 04_Dynamic Programming/img/statevalue.png 1000.89 KB
Part 08-Module 01-Lesson 02_Regression/21. Polynomial Regression-DBhWG-PagEQ.mp4 982.28 KB
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/08. 为何是神经网络-zAkzOZntK6Y.mp4 982.27 KB
Part 08-Module 01-Lesson 02_Regression/05. Moving A Line-8EIHFyL2Log.mp4 981.31 KB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/img/screen-shot-2017-12-04-at-11.14.30-am.png 980.68 KB
Part 02-Module 01-Lesson 03_Training Neural Networks/14. Learning Rate-TwJ8aSZoh2U.mp4 927.05 KB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/img/screen-shot-2017-12-10-at-9.12.16-pm.png 898.01 KB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/img/nature.png 893.03 KB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.mp4 888.58 KB
img/dl-classroom-1200x900.jpg 875.27 KB
Part 08-Module 01-Lesson 02_Regression/14. DLND REG 13 Absolute Vs Squared Error 3 V1 (1)-bIVGf_dDkrY.mp4 873.14 KB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/img/screen-shot-2017-12-04-at-12.49.13-pm.png 871.76 KB
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.mp4 862.5 KB
Part 01-Module 01-Lesson 03_Applying Deep Learning/img/chi-waves.png 823.61 KB
Part 02-Module 01-Lesson 03_Training Neural Networks/09. Local Minima-gF_sW_nY-xw.mp4 819.86 KB
Part 06-Module 01-Lesson 07_Solve OpenAI Gym's Taxi-v2 Task/img/open-terminal.gif 819.23 KB
Part 04-Module 01-Lesson 01_Recurrent Neural Networks/img/screen-shot-2017-12-04-at-12.49.52-pm.png 806.66 KB
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Part 02-Module 01-Lesson 01_Introduction to Neural Networks/img/student-quiz.png 748.98 KB
Part 06-Module 01-Lesson 05_Monte Carlo Methods/img/screen-shot-2017-10-04-at-4.58.58-pm.png 716 KB
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Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.en.vtt 505 B
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.pt-BR.vtt 501 B
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.en.vtt 495 B
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.zh-CN.vtt 487 B
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.pt-BR.vtt 482 B
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.zh-CN.vtt 481 B
Part 02-Module 01-Lesson 03_Training Neural Networks/10. Random Restart-idyBBCzXiqg.pt-BR.vtt 478 B
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/28. Mini Project Introduction-Rgf3YVFWl-M.zh-CN.vtt 475 B
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.pt-BR.vtt 472 B
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.zh-CN.vtt 468 B
Part 02-Module 01-Lesson 03_Training Neural Networks/10. Random Restart-idyBBCzXiqg.en.vtt 466 B
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.zh-CN.vtt 456 B
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.en.vtt 420 B
Part 03-Module 01-Lesson 08_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.pt-BR.vtt 420 B
Part 02-Module 01-Lesson 03_Training Neural Networks/10. Random Restart-idyBBCzXiqg.zh-CN.vtt 419 B
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.zh-CN.vtt 390 B
Part 02-Module 01-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.pt-BR.vtt 364 B
How you can help Team-FTU.txt 241 B
[FreeCoursesOnline.Me].url 133 B
[FreeTutorials.Eu].url 129 B
FTUApps.com website coming soon.txt 94 B
Part 08-Module 02-Lesson 01_MiniFlow/07. Pixels are Features!-qE5YYXtPq9U.pt-BR.vtt 91 B
Part 08-Module 02-Lesson 01_MiniFlow/07. Pixels are Features!-qE5YYXtPq9U.en-US.vtt 72 B
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