1-Udacity - Deep Reinforcement Learning Nanodegree nd893 v1.0.0
File List
- Part 02-Module 01-Lesson 02_Deep Q-Networks/03. Experience Replay-wX_-SZG-YMQ.mp4 48.4 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/12. A2c Export V1-LiUBJje2N0c.mp4 38.6 MB
- Part 06-Module 01-Lesson 03_Deep Learning with PyTorch/04. Py Part 2 V1-u50_ZyKqt8g.mp4 34.6 MB
- Part 01-Module 01-Lesson 11_RL in Continuous Spaces/02. Introduction-GPjK124RU5g.mp4 33.2 MB
- Part 03-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/02. Meet Chris-0ccflD9x5WU.mp4 32.5 MB
- Part 03-Module 01-Lesson 02_Introduction to Policy-Based Methods/11. M2L3 02 V2-ToS8vXGdODE.mp4 32.5 MB
- Part 05-Module 01-Lesson 01_Dynamic Programming/14. Policy Improvement-4_adUEK0IHg.mp4 30.4 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/16. DDPG Export V1-08V9r3NgFSE.mp4 30.4 MB
- Part 04-Module 01-Lesson 03_Case Study AlphaZero/07. TicTacToe using AlphaZero - notebook walkthrough-uUFuBscf98I.mp4 29.3 MB
- Part 01-Module 01-Lesson 11_RL in Continuous Spaces/13. Linear Function Approximation-OJ5wrB7o-pI.mp4 28.7 MB
- Part 06-Module 01-Lesson 03_Deep Learning with PyTorch/05. Py Part 3 V2-u8hDj5aJK6I.mp4 28.4 MB
- Part 03-Module 01-Lesson 07_Continuous Control/img/output.gif 28.3 MB
- Part 05-Module 01-Lesson 01_Dynamic Programming/05. An Iterative Method-AX-hG3KvwzY.mp4 27.6 MB
- Part 06-Module 01-Lesson 03_Deep Learning with PyTorch/07. Py Part 5 V2-coBbbrGZXI0.mp4 27.1 MB
- Part 04-Module 01-Lesson 03_Case Study AlphaZero/07. Alphazero python classes walkthrough-hKnBQvtJ_zQ.mp4 26.9 MB
- Part 05-Module 01-Lesson 01_Dynamic Programming/08. Iterative Policy Evaluation-eDXIL_oOJHI.mp4 26.6 MB
- Part 03-Module 01-Lesson 07_Continuous Control/img/image8.gif 26.5 MB
- Part 08-Module 02-Lesson 01_C++ Intro to Optimization/04. Nd113 Embedded Terminal V1-Bhl5JQ_N9V8.mp4 26.5 MB
- Part 02-Module 01-Lesson 02_Deep Q-Networks/02. Deep Q-Networks-GgtR_d1OB-M.mp4 25.7 MB
- Part 02-Module 02-Lesson 02_Optimize Your GitHub Profile/14. Interview with Art - Part 3-M6PKr3S1rPg.mp4 25.0 MB
- Part 06-Module 01-Lesson 03_Deep Learning with PyTorch/10. Py Part 8 V1-3eqn5sgCOsY.mp4 24.9 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/10. M3 L5 10 A3C Asynchronous Advantage ActorCritic Offpolicy Vs Onpolicy V1-AZiy5R0DESU.mp4 23.3 MB
- Part 02-Module 02-Lesson 02_Optimize Your GitHub Profile/05. Interview with Art - Part 1-ClLYamtaO-Q.mp4 21.8 MB
- Part 01-Module 01-Lesson 11_RL in Continuous Spaces/03. Discrete vs. Continuous Spaces-uHstLeRzaE8.mp4 21.4 MB
- Part 03-Module 01-Lesson 02_Introduction to Policy-Based Methods/06. M2L3 04 V1-QicxmyE5vTo.mp4 21.0 MB
- Part 02-Module 01-Lesson 02_Deep Q-Networks/04. Fixed Q-Targets-SWpyiEezfp4.mp4 21.0 MB
- Part 01-Module 01-Lesson 09_Temporal-Difference Methods/01. Introduction-yXErXQulI_o.mp4 20.7 MB
- Part 03-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/03. Elevator Pitch-S-nAHPrkQrQ.mp4 20.6 MB
- Part 01-Module 01-Lesson 07_The RL Framework The Solution/02. Policies-hc3LrvaC13U.mp4 20.2 MB
- Part 01-Module 01-Lesson 11_RL in Continuous Spaces/12. Function Approximation-UTGWVY6jEdg.mp4 20.1 MB
- Part 06-Module 01-Lesson 02_Convolutional Neural Networks/04. Convolutional Layers (Part 2)-LX-yVob3c28.mp4 19.9 MB
- Part 02-Module 01-Lesson 02_Deep Q-Networks/05. Deep Q-Learning Algorithm-MqTXoCxQ_eY.mp4 17.4 MB
- Part 03-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/01. Why Network-exjEm9Paszk.mp4 17.4 MB
- Part 03-Module 01-Lesson 04_Proximal Policy Optimization/07. pong with REINFORCE walkthrough-eKIjPrQWIgg.mp4 17.4 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/06. M3 L5 06 Policybased Valuebased And ActorCritic V1-iyin896PNEc.mp4 16.9 MB
- Part 01-Module 01-Lesson 09_Temporal-Difference Methods/06. TD Control Sarsamax-4DxoYuR7aZ4.mp4 16.5 MB
- Part 01-Module 01-Lesson 01_Welcome to Deep Reinforcement Learning/04. Unity Machine Learning Agents-jC12h4UAxqs.mp4 16.5 MB
- Part 06-Module 01-Lesson 03_Deep Learning with PyTorch/08. Py Part 6 V1-HiTih59dCWQ.mp4 15.9 MB
- Part 05-Module 01-Lesson 01_Dynamic Programming/23. Value Iteration-XNeQn8N36y8.mp4 15.6 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/08. M3 L5 08 A3C Asynchronous Advantage ActorCritic V2-twNXFplIAP8.mp4 15.0 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/17. MDPs, Part 3-UlXHFbla3QI.mp4 14.7 MB
- Part 02-Module 01-Lesson 03_Deep RL for Robotics/09. Jetson Overview-i56qM6NNW9A.mp4 14.6 MB
- Part 06-Module 01-Lesson 03_Deep Learning with PyTorch/09. PyTorch - Part 7-hFu7GTfRWks.mp4 14.6 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/11. Discounted Return-opXGNPwwn7g.mp4 14.3 MB
- Part 04-Module 01-Lesson 03_Case Study AlphaZero/09. Alphazero advanced tictactoe walkthrough-MOIk_BbCjRw.mp4 14.2 MB
- Part 05-Module 01-Lesson 01_Dynamic Programming/20. Truncated Policy Iteration-a-RvCxlPMho.mp4 14.1 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/05. M3 L5 05 Baselines And Critics V1-wqmqoiUuQHI.mp4 14.0 MB
- Part 06-Module 01-Lesson 03_Deep Learning with PyTorch/03. Part 1 V2-n4mbZYIfKb4.mp4 13.8 MB
- Part 01-Module 01-Lesson 08_Monte Carlo Methods/17. M1 L6 S2 V1-6E_3NJcoxmU.mp4 13.8 MB
- Part 01-Module 01-Lesson 08_Monte Carlo Methods/09. MC Prediction - Solution Walkthrough-Pwiqk7Pncgc.mp4 13.7 MB
- Part 02-Module 02-Lesson 02_Optimize Your GitHub Profile/10. Interview with Art - Part 2-Vvzl2J5K7-Y.mp4 13.2 MB
- Part 08-Module 01-Lesson 01_C++ Getting Started/15. Two Functions Same Name-9SgmzOfBmRU.mp4 13.2 MB
- Part 08-Module 02-Lesson 02_C++ Optimization Practice/16. Nd113 Story 1 V1-lIe2zso8A-w.mp4 12.8 MB
- Part 01-Module 01-Lesson 11_RL in Continuous Spaces/05. Discretization-j2eZyUpy--E.mp4 12.5 MB
- Part 01-Module 01-Lesson 08_Monte Carlo Methods/16. MC Control Constant-alpha-QFV1nI9Zpoo.mp4 12.5 MB
- Part 08-Module 01-Lesson 01_C++ Getting Started/04. Why C++-_t4ZvwfnuCA.mp4 12.0 MB
- Part 08-Module 01-Lesson 01_C++ Getting Started/16. Function Signatures 1-T6kQ_4w98IQ.mp4 11.6 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/13. M3 L5 13 GAE Generalized Advantage Estimation V2-oLFocWp0dt0.mp4 11.3 MB
- Part 01-Module 01-Lesson 11_RL in Continuous Spaces/08. Tile Coding-BRs7AnTZ_8k.mp4 11.0 MB
- Part 08-Module 01-Lesson 04_C++ Object Oriented Programming/03. Why Use Object Oriented Programming-G2KzZfNu9Ak.mp4 10.6 MB
- Part 08-Module 01-Lesson 01_C++ Getting Started/06. Static Vs Dynamic Typing-D7v6iIAORkE.mp4 10.5 MB
- Part 03-Module 01-Lesson 06_Deep RL for Finance (Optional)/04. M3L04 Advantages Of Reinforcemnt Learning For Trading RENDER V1-rqHL4BZocI8.mp4 10.4 MB
- Part 01-Module 01-Lesson 11_RL in Continuous Spaces/11. Coarse Coding-Uu1J5KLAfTU.mp4 10.3 MB
- Part 01-Module 01-Lesson 01_Welcome to Deep Reinforcement Learning/img/output.gif 10.2 MB
- Part 02-Module 01-Lesson 01_Study Plan/img/output.gif 10.2 MB
- Part 02-Module 01-Lesson 03_Deep RL for Robotics/img/output.gif 10.2 MB
- Part 02-Module 02-Lesson 01_Opportunities in Deep Reinforcement Learning/02. Career Services-cuKecPpZ7PM.mp4 10.1 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/03. Episodic vs. Continuing Tasks-E1I-BPanSM8.mp4 10.1 MB
- Part 03-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/04. Elevator Pitch-0QtgTG49E9I.mp4 10.0 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/10. Cumulative Reward-ysriH65lV9o.mp4 10.0 MB
- Part 01-Module 01-Lesson 11_RL in Continuous Spaces/16. Summary-MTEBk43oByU.mp4 9.9 MB
- Part 03-Module 01-Lesson 06_Deep RL for Finance (Optional)/03. M3L603 Challenges Of Supervised Learning RENDER V1-_hAPnbDtteM.mp4 9.8 MB
- Part 03-Module 01-Lesson 06_Deep RL for Finance (Optional)/02. M3L602 High Frequency Trading HFT RENDER V2-oM1zZdZ-8fE.mp4 9.6 MB
- Part 02-Module 02-Lesson 02_Optimize Your GitHub Profile/02. Introduction-Vnj2VNQROtI.mp4 9.6 MB
- Part 06-Module 01-Lesson 02_Convolutional Neural Networks/19. 06 First Convolutional Layer T1 V1 RENDER V2-hIHDMWVSfsM.mp4 9.5 MB
- Part 03-Module 01-Lesson 03_Policy Gradient Methods/05. M3L3 C05 V2-o6CI2q3IXEs.mp4 9.2 MB
- Part 02-Module 01-Lesson 02_Deep Q-Networks/img/sonic.gif 9.1 MB
- Part 03-Module 01-Lesson 06_Deep RL for Finance (Optional)/10. M3L611 Trading Lists SC V1-cGT-ADpHR74.mp4 9.0 MB
- Part 03-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/04. Pitching to a Recruiter-LxAdWaA-qTQ.mp4 8.9 MB
- Part 01-Module 01-Lesson 11_RL in Continuous Spaces/14. Kernel Functions-RdkPVYyVOvU.mp4 8.9 MB
- Part 06-Module 01-Lesson 02_Convolutional Neural Networks/img/embedding.gif 8.7 MB
- Part 03-Module 01-Lesson 06_Deep RL for Finance (Optional)/09. M3L610 Almgren And Chriss Model SC V1-rokcEQ4LXbU.mp4 8.7 MB
- Part 01-Module 01-Lesson 05_Introduction to RL/02. Applications-CV6B84mKRNM.mp4 8.5 MB
- Part 01-Module 01-Lesson 01_Welcome to Deep Reinforcement Learning/01. Welcome To DRLND-i1-l0n1ntes.mp4 8.4 MB
- Part 03-Module 01-Lesson 04_Proximal Policy Optimization/13. Pong with PPO walkthrough-XhfhR7Z01S0.mp4 8.3 MB
- Part 03-Module 01-Lesson 03_Policy Gradient Methods/img/grad-descent.gif 8.3 MB
- Part 01-Module 01-Lesson 08_Monte Carlo Methods/03. L603 Monte Carlo Methods RENDER V3-2-titaMCRl224.mp4 8.3 MB
- Part 03-Module 01-Lesson 06_Deep RL for Finance (Optional)/11. M3L612 The Efficient Frontier V1-EwM7Ksbs-ds.mp4 8.2 MB
- Part 05-Module 01-Lesson 01_Dynamic Programming/17. Policy Iteration-gqv7o1kBDc0.mp4 8.1 MB
- Part 08-Module 01-Lesson 01_C++ Getting Started/17. Function Signatures 2-Sx4AWTmXl2U.mp4 8.1 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/17. M3L517 Summary HS 1 V1-rRuiMhijw_s.mp4 8.1 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/01. M3L501 Introduction HS 1 V1-_OHo1pEaJcQ.mp4 8.0 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/08. Goals and Rewards, Part 2-pVIFc72VYH8.mp4 8.0 MB
- Part 04-Module 01-Lesson 03_Case Study AlphaZero/05. AlphaZero 1 Guided Tree Search-LinuRy47xbw.mp4 8.0 MB
- Part 08-Module 01-Lesson 03_Practical C++/01. Introduction To Compilation-dyzGEB8YDGg.mp4 8.0 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/14. M3 L5 14 DDPG Deep Deterministic Policy Gradient Continuous Actionspace V1-0NVOPIyrr98.mp4 7.8 MB
- Part 01-Module 01-Lesson 12_What's Next/01. Arpan Rollercoaster-Rf6cCYRqV58.mp4 7.8 MB
- Part 08-Module 02-Lesson 01_C++ Intro to Optimization/02. C Opt 01 L V2-Kdx1_BI5ddc.mp4 7.8 MB
- Part 01-Module 01-Lesson 05_Introduction to RL/03. The Setting-nh8Gwdu19nc.mp4 7.8 MB
- Part 06-Module 01-Lesson 01_Neural Networks/11. Regularization-ndYnUrx8xvs.mp4 7.6 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/img/chess-game.jpg 7.5 MB
- Part 03-Module 01-Lesson 06_Deep RL for Finance (Optional)/08. M3L609 Optimization SC PT4 V2-N2LP-wg1jEI.mp4 7.4 MB
- Part 03-Module 01-Lesson 03_Policy Gradient Methods/01. M3L3 C01 V3-ZEhQRASU5O4.mp4 7.4 MB
- Part 08-Module 01-Lesson 01_C++ Getting Started/02. Lesson Overview C++-lR3PH3bL-9U.mp4 7.4 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/02. The Setting, Revisited-V6Q1uF8a6kA.mp4 7.4 MB
- Part 02-Module 01-Lesson 01_Study Plan/02. Deep RL in Robotics-IjG_IWJdb1w.mp4 7.3 MB
- Part 02-Module 01-Lesson 02_Deep Q-Networks/13. Summary-x6JggcDTcys.mp4 7.2 MB
- Part 02-Module 01-Lesson 03_Deep RL for Robotics/02. 02 Welcome!-1oElWzRt-lU.mp4 7.2 MB
- Part 01-Module 01-Lesson 07_The RL Framework The Solution/11. Optimal Policies-2rguYpVyCto.mp4 7.1 MB
- Part 01-Module 01-Lesson 05_Introduction to RL/04. Resources-_YPqfAnCqtk.mp4 7.0 MB
- Part 02-Module 02-Lesson 02_Optimize Your GitHub Profile/09. Writing READMEs with Walter-DQEfT2Zq5_o.mp4 6.9 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/07. Goals and Rewards, Part 1-XPnj3Ya3EuM.mp4 6.8 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/14. MDPs, Part 2-CUTtQvxKkNw.mp4 6.8 MB
- Part 04-Module 01-Lesson 03_Case Study AlphaZero/04. Monte Carlo Tree Search 2 - Expansion and Back-propagation-H34Wtk1iNDY.mp4 6.8 MB
- Part 04-Module 01-Lesson 03_Case Study AlphaZero/01. Alpha Zero Preview-Zzc1XJ1aJ-4.mp4 6.8 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/15. M3 L5 15 DDPG Deep Deterministic Policy Gradient Soft Updates V1-RT-HDnAVe9o.mp4 6.6 MB
- Part 01-Module 01-Lesson 07_The RL Framework The Solution/09. Action-Value Functions-KJLaRfOOPGA.mp4 6.6 MB
- Part 06-Module 01-Lesson 01_Neural Networks/05. Backpropagation V2-1SmY3TZTyUk.mp4 6.5 MB
- Part 03-Module 01-Lesson 03_Policy Gradient Methods/03. M3L3 C03 V2-dJz_p4FKE-g.mp4 6.5 MB
- Part 03-Module 01-Lesson 03_Policy Gradient Methods/02. M3L3 C02 V6-zoOgRoaxGiU.mp4 6.5 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/02. M3 L5 02 Motivation V1-dpFPlDtdxyQ.mp4 6.5 MB
- Part 06-Module 01-Lesson 01_Neural Networks/08. Underfitting And Overfitting-xj4PlXMsN-Y.mp4 6.4 MB
- Part 04-Module 01-Lesson 03_Case Study AlphaZero/03. Monte Carlo Tree Search 1 - Random Sampling-wn2B3j_Qz6E.mp4 6.3 MB
- Part 05-Module 01-Lesson 01_Dynamic Programming/01. Introduction-ek2PD9RDrWw.mp4 6.2 MB
- Part 02-Module 01-Lesson 03_Deep RL for Robotics/09. 09 Jetson TX2 Edits V1-M26z7vTti_g.mp4 6.1 MB
- Part 08-Module 01-Lesson 01_C++ Getting Started/15. Two Functions Same Name-0ZF649G58l4.mp4 6.1 MB
- Part 08-Module 01-Lesson 01_C++ Getting Started/01. Introduction-ahoiVrq4qAk.mp4 6.0 MB
- Part 01-Module 01-Lesson 07_The RL Framework The Solution/08. Optimality-j231aRV74QM.mp4 6.0 MB
- Part 04-Module 01-Lesson 02_Introduction to Multi-Agent RL/09. M4 L2 C08 Cooperation Competition Mixed Environments A V1-vx6PIH5_oFg.mp4 5.9 MB
- Part 02-Module 01-Lesson 02_Deep Q-Networks/10. 10 Prioritized Experience Replay V1-cN8z-7Ze9L8.mp4 5.9 MB
- Part 08-Module 01-Lesson 01_C++ Getting Started/02. Nd113 C3 L1 04 L Lesson Overview 2 V1-DjT2E23xhj8.mp4 5.8 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/04. M3 L5 04 Two Ways For Estimating Expected Returns V3-2W6yIBDvfsQ.mp4 5.8 MB
- Part 06-Module 01-Lesson 02_Convolutional Neural Networks/08. Pooling Layers-OkkIZNs7Cyc.mp4 5.8 MB
- Part 06-Module 01-Lesson 01_Neural Networks/05. DL 46 Calculating The Gradient 2 V2 (2)-7lidiTGIlN4.mp4 5.7 MB
- Part 03-Module 01-Lesson 04_Proximal Policy Optimization/09. Importance Sampling-cYPvWriOPIk.mp4 5.7 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/03. M3 L5 03 Bias And Variance V2-_vnkkwm46uU.mp4 5.7 MB
- Part 02-Module 01-Lesson 04_Navigation/img/bananas-save.gif 5.6 MB
- Part 01-Module 01-Lesson 07_The RL Framework The Solution/01. Introduction-9Wyf5Zsska8.mp4 5.4 MB
- Part 08-Module 02-Lesson 01_C++ Intro to Optimization/07. 03 L Binary V1 RENDER V1-K6CpHxnhc2s.mp4 5.4 MB
- Part 06-Module 01-Lesson 01_Neural Networks/04. DL 41 Feedforward FIX V2-hVCuvMGOfyY.mp4 5.3 MB
- Part 01-Module 01-Lesson 01_Welcome to Deep Reinforcement Learning/02. RL In The Real World-IGlAyGbOTHo.mp4 5.3 MB
- Part 01-Module 01-Lesson 07_The RL Framework The Solution/05. State-Value Functions-llakAjwox_8.mp4 5.3 MB
- Part 03-Module 01-Lesson 04_Proximal Policy Optimization/11. PPO Part 2 Clipping Policy Updates-NRzjGGX6c34.mp4 5.3 MB
- Part 01-Module 01-Lesson 01_Welcome to Deep Reinforcement Learning/img/soccer.gif 5.2 MB
- Part 01-Module 01-Lesson 05_Introduction to RL/01. Introduction-6jSFl5kxIBs.mp4 5.2 MB
- Part 04-Module 01-Lesson 03_Case Study AlphaZero/06. Alpha Zero 2 Self-Play Training-wl1qfPXqRuQ.mp4 5.1 MB
- Part 08-Module 01-Lesson 01_C++ Getting Started/10. Doubles Are Bigger-uhwTWgmM2iY.mp4 5.1 MB
- Part 04-Module 01-Lesson 02_Introduction to Multi-Agent RL/08. M4 L2 C07 Approaches To MARL V1-uKV9AJykin0.mp4 5.1 MB
- Part 06-Module 01-Lesson 02_Convolutional Neural Networks/02. 03 Data And Lesson Outline RENDER V2-jPr-5aZA6NE.mp4 5.0 MB
- Part 03-Module 01-Lesson 02_Introduction to Policy-Based Methods/04. M3 L2 C04 V3-5E86a0OyVyI.mp4 5.0 MB
- Part 01-Module 01-Lesson 11_RL in Continuous Spaces/15. Non-Linear Function Approximation-rITnmpD2mN8.mp4 4.9 MB
- Part 06-Module 01-Lesson 01_Neural Networks/09. Model Complexity Graph-NnS0FJyVcDQ.mp4 4.9 MB
- Part 04-Module 01-Lesson 03_Case Study AlphaZero/02. Zero-Sum Game-uPw1dHVqdXQ.mp4 4.9 MB
- Part 02-Module 01-Lesson 02_Deep Q-Networks/01. DQN Overview-WgiAvr7COR0.mp4 4.9 MB
- Part 01-Module 01-Lesson 08_Monte Carlo Methods/04. L604 MC Prediction Part 1RENDER V2-6ts9gdIS6vg.mp4 4.8 MB
- Part 04-Module 01-Lesson 02_Introduction to Multi-Agent RL/05. M4 L2 C05 Benefits Of Multi Agent Systems V2-NXDv9cEZTaw.mp4 4.8 MB
- Part 06-Module 01-Lesson 01_Neural Networks/03. Combinando modelos-Boy3zHVrWB4.mp4 4.7 MB
- Part 05-Module 01-Lesson 01_Dynamic Programming/04. Another Gridworld Example-n9SbomnLb-U.mp4 4.7 MB
- Part 01-Module 01-Lesson 08_Monte Carlo Methods/12. L612 Epsilon Greedy Policies RENDER V4-PxJMtlR06MY.mp4 4.7 MB
- Part 02-Module 01-Lesson 03_Deep RL for Robotics/01. 01 Introduction RENDER V2-dfeawuScC7k.mp4 4.7 MB
- Part 04-Module 01-Lesson 02_Introduction to Multi-Agent RL/06. M4 L2 C06 Markov Games 2 V1-Y9qq4Jqnwls.mp4 4.6 MB
- Part 04-Module 01-Lesson 02_Introduction to Multi-Agent RL/03. M4 L2 C03 Motivation For Multi Agent Systems V1-i_s22qgQYL4.mp4 4.6 MB
- Part 06-Module 01-Lesson 02_Convolutional Neural Networks/17. 04 Feature Visualization V1 RENDER V2-xwGa7RFg1EQ.mp4 4.5 MB
- Part 08-Module 02-Lesson 01_C++ Intro to Optimization/12. C Opt 05 L V3-rTtZVyWxYG8.mp4 4.5 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/06. The Reward Hypothesis-uAqNwgZ49JE.mp4 4.4 MB
- Part 01-Module 01-Lesson 09_Temporal-Difference Methods/08. TD Control Expected Sarsa-kEKupCyU0P0.mp4 4.3 MB
- Part 08-Module 01-Lesson 04_C++ Object Oriented Programming/01. Introduction-4xHI5LFX-cQ.mp4 4.3 MB
- Part 03-Module 01-Lesson 03_Policy Gradient Methods/04. M3L3 C04 V2-St9ftvMQ_ks.mp4 4.3 MB
- Part 08-Module 02-Lesson 01_C++ Intro to Optimization/03. 02 L Intro To Comp HW V1 RENDER V1-WDMGkq9mkB8.mp4 4.3 MB
- Part 03-Module 01-Lesson 02_Introduction to Policy-Based Methods/01. M3 L2 C01 V2-mMnhi8yzwKk.mp4 4.2 MB
- Part 06-Module 01-Lesson 01_Neural Networks/12. Dropout-Ty6K6YiGdBs.mp4 4.2 MB
- Part 06-Module 01-Lesson 02_Convolutional Neural Networks/15. Dropout-Ty6K6YiGdBs.mp4 4.2 MB
- Part 04-Module 01-Lesson 02_Introduction to Multi-Agent RL/13. M4 L2 C11 Summary HS V1-yGPHGYHqjq8.mp4 4.2 MB
- Part 01-Module 01-Lesson 04_Learning Plan/img/42135602-b0335606-7d12-11e8-8689-dd1cf9fa11a9.gif 4.2 MB
- Part 01-Module 01-Lesson 01_Welcome to Deep Reinforcement Learning/img/banana.gif 4.2 MB
- Part 02-Module 01-Lesson 04_Navigation/img/banana.gif 4.2 MB
- Part 01-Module 01-Lesson 07_The RL Framework The Solution/06. Bellman Equations-UgIaDMvSdUo.mp4 4.1 MB
- Part 04-Module 01-Lesson 02_Introduction to Multi-Agent RL/02. M4 L2 C02 Introduction To Multi Agent Systems V1-ra-w63kzq6I.mp4 4.0 MB
- Part 02-Module 02-Lesson 02_Optimize Your GitHub Profile/07. Quick Fixes-Lb9e2KemR6I.mp4 4.0 MB
- Part 01-Module 01-Lesson 01_Welcome to Deep Reinforcement Learning/img/reacher.gif 4.0 MB
- Part 03-Module 01-Lesson 07_Continuous Control/img/reacher.gif 4.0 MB
- Part 06-Module 01-Lesson 01_Neural Networks/16. Batch vs Stochastic Gradient Descent-2p58rVgqsgo.mp4 4.0 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/07. M3 L5 07 A Basic ActorCritic Agent V2-KdHQ24hBKho.mp4 3.9 MB
- Part 01-Module 01-Lesson 06_The RL Framework The Problem/13. MDPs, Part 1-NBWbluSbxPg.mp4 3.9 MB
- Part 03-Module 01-Lesson 05_Actor-Critic Methods/09. M3 L5 09 A3C Asynchronous Advantage ActorCritic Parallel Training V2-kKRbAKhjACo.mp4 3.8 MB
- Part 02-Module 02-Lesson 02_Optimize Your GitHub Profile/04. Good GitHub repository-qBi8Q1EJdfQ.mp4 3.7 MB
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