Reinforcement Learning Specialization
Reinforcement Learning Specialization metadata, size 4722.68 MB, 699 files, category video, indexed at 2026-05-18.
资源标识
Infohashe00a4fc3f94ef3ff923884f09a47fff540d7ee60
总大小4.6 GB
格式mp4
分类视频
文件数699
发掘时间（北京时间）2026-05-18 15:32:12
最后活跃（北京时间）2026-05-18 15:32:12
下载标识
完整磁力链接
magnet:?xt=urn:btih:e00a4fc3f94ef3ff923884f09a47fff540d7ee60&dn=Reinforcement%20Learning%20Specialization
迅雷地址
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOmUwMGE0ZmMzZjk0ZWYzZmY5MjM4ODRmMDlhNDdmZmY1NDBkN2VlNjAmZG49UmVpbmZvcmNlbWVudCUyMExlYXJuaW5nJTIwU3BlY2lhbGl6YXRpb25aWg==
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文件列表
| 文件名 | 格式 | 大小 |
|---|---|---|
| 04_warren-powell-approximate-dynamic-programming-for-fleet-management-long.mp4 | mp4 | 145.3 MB |
| TutsNode.net.txt | txt | 63 B |
| 01_sequential-decision-making_quiz.html | html | 210.3 KB |
| 01_course-4-introduction.en.txt | txt | 2.3 KB |
| 01_dynamic-programming_quiz.html | html | 157.5 KB |
| 04_read-me-pre-requisites-and-learning-objectives_Course_2__Sample_Based_Learning_Methods_Learning_Objectives.pdf | 83.1 KB | |
| 06_read-me-pre-requisites-and-learning-objectives_Fundamentals_of_Reinforcement_Learning__Learning_Objectives.pdf | 64.7 KB | |
| 03_read-me-pre-requisites-and-learning-objectives_Prediction_and_Control_with_Function_Approximation_Learning_Objectives.pdf | 59.9 KB | |
| 03_reinforcement-learning-textbook_instructions.html | html | 2.2 KB |
| 04_pre-requisites-and-learning-objectives_A_Complete_Reinforcement_Learning_System_Capstone__Learning_Objectives.pdf | 56.8 KB | |
| 04_emma-brunskill-batch-reinforcement-learning.en.srt | srt | 24.9 KB |
| 02_course-introduction.en.txt | txt | 5.6 KB |
| 0 | pad/0 | 14 B |
| 05_reinforcement-learning-textbook_RLbook2018.pdf | 85.3 MB | |
| 04_warren-powell-approximate-dynamic-programming-for-fleet-management-long.en.srt | srt | 40.7 KB |
| 02_graded-value-functions-and-bellman-equations_exam.html | html | 31.1 KB |
| 04_warren-powell-approximate-dynamic-programming-for-fleet-management-long.en.txt | txt | 21.3 KB |
| 02_satinder-singh-on-intrinsic-rewards.en.srt | srt | 21.0 KB |
| 02_michael-littman-the-reward-hypothesis.en.srt | srt | 18.5 KB |
| 03_andy-barto-and-rich-sutton-more-on-the-history-of-rl.en.srt | srt | 15.9 KB |
| 03_meet-your-instructors.en.srt | srt | 15.9 KB |
| 03_lets-review-average-reward-a-new-way-of-formulating-control-problems.en.srt | srt | 15.2 KB |
| 02_lets-review-examples-of-episodic-and-continuing-tasks.en.txt | txt | 2.5 KB |
| 01_average-reward-a-new-way-of-formulating-control-problems.en.srt | srt | 15.2 KB |
| 03_david-silver-on-deep-learning-rl-ai.en.srt | srt | 14.7 KB |
| 01_meeting-with-niko-choosing-the-learning-algorithm.en.txt | txt | 2.8 KB |
| 04_jonathan-langford-contextual-bandits-for-real-world-reinforcement-learning.en.srt | srt | 14.0 KB |
| 01_gradient-descent-for-training-neural-networks.en.srt | srt | 14.0 KB |
| 01_lets-review-expected-sarsa.en.txt | txt | 2.8 KB |
| 04_iterative-policy-evaluation.en.srt | srt | 13.7 KB |
| 02_joelle-pineau-about-rl-that-matters.en.srt | srt | 13.7 KB |
| 02_lets-review-what-is-q-learning.en.txt | txt | 2.6 KB |
| 02_meet-your-instructors.en.srt | srt | 13.4 KB |
| 02_meet-your-instructors.en.srt | srt | 13.4 KB |
| 02_meet-your-instructors.en.srt | srt | 13.4 KB |
| 02_policy-iteration.en.srt | srt | 13.3 KB |
| 04_emma-brunskill-batch-reinforcement-learning.en.txt | txt | 13.2 KB |
| 03_gaussian-policies-for-continuous-actions.en.srt | srt | 12.8 KB |
| 02_andy-barto-on-what-are-eligibility-traces-and-why-are-they-so-named.en.srt | srt | 12.5 KB |
| 01_what-is-the-trade-off.en.srt | srt | 12.2 KB |
| 01_optimal-policies.en.srt | srt | 12.2 KB |
| 03_warren-powell-approximate-dynamic-programming-for-fleet-management-short.en.srt | srt | 12.1 KB |
| 01_mdps_quiz.html | html | 11.8 KB |
| 02_michael-littman-the-reward-hypothesis.en.txt | txt | 11.6 KB |
| 03_doina-precup-building-knowledge-for-ai-agents-with-reinforcement-learning.en.srt | srt | 11.3 KB |
| 04_rich-sutton-the-importance-of-td-learning.en.srt | srt | 11.2 KB |
| 02_satinder-singh-on-intrinsic-rewards.en.txt | txt | 11.0 KB |
| 02_demonstration-with-actor-critic.en.srt | srt | 10.9 KB |
| 03_using-optimal-value-functions-to-get-optimal-policies.en.srt | srt | 10.8 KB |
| 01_agent-architecture-meeting-with-martha-overview-of-design-choices.en.srt | srt | 10.8 KB |
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