{"id":13671237,"url":"https://github.com/AssemblyAI-Community/ML-Study-Guide","last_synced_at":"2025-04-27T14:33:11.246Z","repository":{"id":37467598,"uuid":"505861987","full_name":"AssemblyAI-Community/ML-Study-Guide","owner":"AssemblyAI-Community","description":"Minimal Machine Learning Study Plan","archived":false,"fork":false,"pushed_at":"2024-06-13T05:49:54.000Z","size":14,"stargazers_count":1875,"open_issues_count":4,"forks_count":388,"subscribers_count":50,"default_branch":"main","last_synced_at":"2025-04-09T03:12:11.048Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/AssemblyAI-Community.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":"2022-06-21T13:46:10.000Z","updated_at":"2025-04-02T02:35:59.000Z","dependencies_parsed_at":"2024-06-28T09:47:45.704Z","dependency_job_id":null,"html_url":"https://github.com/AssemblyAI-Community/ML-Study-Guide","commit_stats":null,"previous_names":["assemblyai-community/ml-study-guide","assemblyai-examples/ml-study-guide"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AssemblyAI-Community%2FML-Study-Guide","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AssemblyAI-Community%2FML-Study-Guide/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AssemblyAI-Community%2FML-Study-Guide/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AssemblyAI-Community%2FML-Study-Guide/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AssemblyAI-Community","download_url":"https://codeload.github.com/AssemblyAI-Community/ML-Study-Guide/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251154371,"owners_count":21544489,"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":[],"created_at":"2024-08-02T09:01:03.728Z","updated_at":"2025-04-27T14:33:10.964Z","avatar_url":"https://github.com/AssemblyAI-Community.png","language":null,"funding_links":[],"categories":["Others"],"sub_categories":[],"readme":"# How to get started with ML\n\nThis my recommended study guide to get started with Machine Learning.\n\nWatch the video on [YouTube](https://youtu.be/wtolixa9XTg).\n\n## 1. Math\n\nLearn some math basics! Focus only on these topics, then come back later in case you need to learn more.\n\n * [Khan Academy - Multivariable Calculus](https://www.khanacademy.org/math/multivariable-calculus)\n * [Khan Academy - Differential Equations](https://www.khanacademy.org/math/differential-equations)\n * [Khan Academy - Linear Algebra](https://www.khanacademy.org/math/linear-algebra)\n * [Khan Academy - Statistics Probability](https://www.khanacademy.org/math/statistics-probability)\n * [Optional: 3Blue1Brown - Essence of Linear Algebra](https://www.3blue1brown.com/essence-of-linear-algebra-page/)\n \n## 2. Learn Python\n\n* [4h Beginner Course](https://youtu.be/rfscVS0vtbw)\n* [6h Intermediate Python Programming Course](https://youtu.be/HGOBQPFzWKo)\n\n## 3. Learn The ML Tech Stack:\n\n* NumPy:  [1h NumPy Crash Course](https://youtu.be/9JUAPgtkKpI)\n* Pandas: [1h Pandas Crash Course](https://youtu.be/vmEHCJofslg)\n* Matplotlib: [1h Matplotlib Crash Course Course](https://youtu.be/3Xc3CA655Y4)\n\n(Scikit-Learn and TensorFlow are taught in step 4. PyTorch is optional, maybe in step 7)\n\n## 4. Machine Learning Courses\n\n* [Machine Learning Specialization Andrew Ng | Coursera](https://www.coursera.org/specializations/machine-learning-introduction) (3 Courses)\n* Optional: [Machine Learning From Scratch](https://youtube.com/playlist?list=PLqnslRFeH2Upcrywf-u2etjdxxkL8nl7E)\n\n## 5. Hands-on Data Preparation\n\n* [Kaggle Intro to Machine Learning](https://www.kaggle.com/learn/intro-to-machine-learning)\n* [Kaggle Intermediate Machine Learning](https://www.kaggle.com/learn/intermediate-machine-learning)\n\n## 6. Practise!\n\nSolve Challenges and build your own projects with datasets from [Kaggle.com](Kaggle.com).\n\n## 7. Specialize \u0026 Create Blog\n\n* Specialize in one field (e.g. Computer Vision, NLP, etc.) \n* Look at requirements in corresponding job descriptions and learn those skills\n* Tip: Create a blog and share tutorials and what you have learned!\n\n## Books\nIf you prefer learning with books, these are great recommendations:\n\n* [Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow](https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/)\n* [Machine Learning with PyTorch and Scikit-Learn](https://www.packtpub.com/product/machine-learning-with-pytorch-and-scikit-learn/9781801819312)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FAssemblyAI-Community%2FML-Study-Guide","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FAssemblyAI-Community%2FML-Study-Guide","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FAssemblyAI-Community%2FML-Study-Guide/lists"}