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| 03. Workspaces Best Practices.html |
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| 03. Your Workspace.html |
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| 04. Advantages of RL for Trading.html |
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| 04. Applications of Multi-Agent Systems.html |
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| 04. L604 MC Prediction Part 1RENDER V2-6ts9gdIS6vg.en.vtt |
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| 04. M3L04 Advantages Of Reinforcemnt Learning For Trading RENDER V1-rqHL4BZocI8.mp4 |
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| 06. The Reward Hypothesis.html |
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| 07. A Basic Actor-Critic Agent.html |
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| 07. Exercise If Statements.html |
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| 07. M3 L5 07 A Basic ActorCritic Agent V2-KdHQ24hBKho.mp4 |
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| 07. M3L608 Optimization SC PT3 V1-3pN77gMg788.mp4 |
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| 07. More Black-Box Optimization.html |
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| 07. Optimal Liquidation Problem - Part 3 - Price Model.html |
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| 07. Review Anatomy of a Class.html |
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| 07. Testing.html |
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| 08. 1D Vector Playground.html |
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| 08. A3C Asynchronous Advantage Actor-Critic, N-step.html |
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| 08. Approaches to MARL.html |
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| 08. Arm Sample.html |
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| 08. Basic Data Types.html |
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| 08. Coding Exercise.html |
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| 08. Collaborate!.html |
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| 08. Community Guidelines.html |
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| 08. For Loops.html |
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| 08. M3 L5 08 A3C Asynchronous Advantage ActorCritic V2-twNXFplIAP8.mp4 |
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| 08. M3L609 Optimization SC PT4 V2-N2LP-wg1jEI.mp4 |
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| 08. Optimal Liquidation Problem - Part 4 - Expected Shortfall.html |
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| 08. Saving and Loading Trained Networks.html |
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| 08. Work Experiences Accomplishments.html |
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| 08. Workspace.html |
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| 08. Workspace - Introduction.html |
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| 09. 09 Jetson TX2 Edits V1-M26z7vTti_g.en.vtt |
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| 09. 10 Double DQN V2-PGCEMLujiGI.en.vtt |
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| 09. 2D Vectors.html |
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| 09. A3C Asynchronous Advantage Actor-Critic, Parallel Training.html |
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| 09. Advanced TicTacToe using AlphaZero.html |
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| 09. Alphazero advanced tictactoe walkthrough-MOIk_BbCjRw.mp4 |
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| 09. Build and Strengthen Your Network.html |
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| 09. Collaborate!.html |
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| 09. Cooperation, Competition, Mixed Environments.html |
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| 09. Demo Binary Floats.html |
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| 09. Jetson Overview-i56qM6NNW9A.en.vtt |
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| 09. Jetson Overview-i56qM6NNW9A.mp4 |
14.64MB |
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| 09. Loading Data Sets with Torchvision.html |
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| 09. M3 L5 09 A3C Asynchronous Advantage ActorCritic Parallel Training V2-kKRbAKhjACo.mp4 |
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| 09. M3L610 Almgren And Chriss Model SC V1-rokcEQ4LXbU.mp4 |
8.65MB |
| 09. M4 L2 C08 Cooperation Competition Mixed Environments A V1-vx6PIH5_oFg.en.vtt |
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| 09. MC Prediction - Solution Walkthrough-Pwiqk7Pncgc.en.vtt |
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| 09. Model Complexity Graph-NnS0FJyVcDQ.en.vtt |
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| 09. Notebook Visualizing a Pooling Layer.html |
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| 09. PyTorch - Part 7-hFu7GTfRWks.en.vtt |
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| 09. Quiz Expected Sarsa.html |
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| 09. Quiz Goals and Rewards.html |
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| 09. What's Next.html |
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| 09. Workspace.html |
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| 09. Writing READMEs with Walter.html |
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| 10. (Optional) Challenge Learning from Pixels.html |
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| 10. 04 L C And RAM V1 RENDER V1-60jEbKV1UOI.en.vtt |
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| 10. 10 Prioritized Experience Replay V1-cN8z-7Ze9L8.en.vtt |
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| 10. 10 Summary HS V3-cb1FGgZIitc.en.vtt |
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| 10. Doubles are Bigger.html |
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| 10. Fully-Connected Layers, VGG-16.html |
10.70KB |
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| 10. Intermediate Variables.html |
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| 10. Interview with Art - Part 2.html |
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| 10. M3 L5 10 A3C Asynchronous Advantage ActorCritic Offpolicy Vs Onpolicy V1-AZiy5R0DESU.mp4 |
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| 10. M3L611 Trading Lists SC V1-cGT-ADpHR74.mp4 |
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| 10. M4 L2 C09 Paper Description Part I HSAEG V1-nRKrQamUISs.en.vtt |
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| 10. Prioritized Experience Replay.html |
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| 10. Quiz Action-Value Functions.html |
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| 10. Regularization.html |
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| 10. Summary.html |
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| 10. Trading Lists.html |
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| 10. Workspace.html |
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| 10. Workspace Tile Coding.html |
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| 11. 10 Dueling DQN V2-zZeHbPs39Ls.en.vtt |
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| 11. Notebook Visualizing FashionMNIST.html |
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| 11. OpenAI Gym CliffWalkingEnv.html |
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| 11. Optimal Policies.html |
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| 11. Paper Description, Part 1.html |
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| 11. The Efficient Frontier.html |
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| 11. Why Policy-Based Methods.html |
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| 12. A2C Code Walk-through.html |
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| 12. A2c Export V1-LiUBJje2N0c.mp4 |
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| 12. L612 Epsilon Greedy Policies RENDER V4-PxJMtlR06MY.en.vtt |
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| 12. Next Lesson.html |
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| 12. Outro.html |
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| 12. Paper Description, Part 2.html |
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| 12. Quiz Optimal Policies.html |
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| 12. Quiz Pole-Balancing.html |
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| 12. Summary.html |
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| 12. TLPPO Summary V1-qRAUAAWA_kc.mp4 |
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| 12. Training in PyTorch.html |
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| 12. Up Next.html |
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| 12. Vector Storage.html |
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| 12. Workspace - Introduction.html |
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| 13. Anatomy of a Function.html |
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| 13. Class Variables.html |
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| 13. Coding Exercise.html |
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| 13. Exercise Vector Storage.html |
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| 13. GAE Generalized Advantage Estimation.html |
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| 13. Mini Project DP (Part 2).html |
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| 13. Notebook Fashion MNIST Training Exercise.html |
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| 13. pong with PPO (code walkthrough).html |
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| 13. Summary.html |
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| 14. Class Function Declarations.html |
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| 14. DDPG Deep Deterministic Policy Gradient, Continuous Actions.html |
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| 14. Exploration vs. Exploitation.html |
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| 14. Interview with Art - Part 3.html |
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| 14. Kernel Functions.html |
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| 14. Lab Instructions.html |
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| 14. Multiple Outputs.html |
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| 14. Notebook FashionMNIST, Solution 1.html |
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| 14. pong with PPO (workspace).html |
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| 14. References.html |
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| 15. Constructor Functions.html |
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| 15. DDPG Deep Deterministic Policy Gradient, Soft Updates.html |
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| 15. Exercise References.html |
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| 15. M3 L5 15 DDPG Deep Deterministic Policy Gradient Soft Updates V1-RT-HDnAVe9o.mp4 |
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| 15. MADDPG - Lab.html |
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| 15. Other Activation Functions.html |
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| sigmoid-derivative.gif |
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| soccer.gif |
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| soccer.png |
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| sonic.gif |
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| speaking.png |
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| t-sne-mnist.png |
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