{"id":22064601,"url":"https://github.com/adeshpande3/machine-learning-notes","last_synced_at":"2025-03-23T18:13:35.555Z","repository":{"id":134025263,"uuid":"90399903","full_name":"adeshpande3/Machine-Learning-Notes","owner":"adeshpande3","description":"Notes for several Machine Learning and Deep Learning courses, textbooks, and talks","archived":false,"fork":false,"pushed_at":"2018-10-02T06:22:38.000Z","size":906,"stargazers_count":58,"open_issues_count":1,"forks_count":30,"subscribers_count":5,"default_branch":"master","last_synced_at":"2025-01-28T23:51:56.030Z","etag":null,"topics":["machine-learning","notes"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/adeshpande3.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2017-05-05T17:19:48.000Z","updated_at":"2024-06-18T08:26:51.000Z","dependencies_parsed_at":null,"dependency_job_id":"6922ed27-e689-4954-86f4-00e6be086e81","html_url":"https://github.com/adeshpande3/Machine-Learning-Notes","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adeshpande3%2FMachine-Learning-Notes","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adeshpande3%2FMachine-Learning-Notes/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adeshpande3%2FMachine-Learning-Notes/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adeshpande3%2FMachine-Learning-Notes/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/adeshpande3","download_url":"https://codeload.github.com/adeshpande3/Machine-Learning-Notes/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245144973,"owners_count":20568056,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["machine-learning","notes"],"created_at":"2024-11-30T19:12:51.428Z","updated_at":"2025-03-23T18:13:35.532Z","avatar_url":"https://github.com/adeshpande3.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine-Learning-Notes\nNotes for several Machine Learning and Deep Learning courses and textbooks and talks.\n\n* **Reinforcement Learning Course** - This lecture course is taught by David Silver of Google Deepmind. The lectures can be found on YouTube at this [link](https://www.youtube.com/watch?v=2pWv7GOvuf0\u0026list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT). In this course, you'll learn about the following topics. \n  - Markov Decision Processes \n  - Value functions \n  - Policies\n  - Dynamic programming approaches\n  - Monte Carlo learning\n  - Temporal difference learning\n  - SARSA\n  - Value function approximation\n  - Policy gradients\n  - Deep Q networks\n  \n* **Scaled Machine Learning Conference Notes** - These were the notes I took at the Scaled ML conference at Stanford. Here is a link to [event page](http://scaledml.org/). \n\n* **Machine Learning: A Probabilistic Perspective Notes** - ML textbook with an emphasis on describing concepts with relation to probability. \n\n* **Elements of Statistical Learning Notes** - Another hard ML textbook with an emphasis on a lot of the math behind traditional ML models. \n\n* **The AI Conference 2017 Notes** - These were the notes I took at The AI Conference sponsored by O'Reilly Media. Here is a link to [event page](https://conferences.oreilly.com/artificial-intelligence/ai-ca). \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadeshpande3%2Fmachine-learning-notes","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadeshpande3%2Fmachine-learning-notes","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadeshpande3%2Fmachine-learning-notes/lists"}