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All implementations are written using just NumPy.\n\n\u003e [!WARNING]\n\u003e This repo is in heavy development.\n\u003e I am to also provide derivations and insights that I deem important that don't exist in the official lecture notes.\n\n\nTo run a model locally, simply call:\n```bash\nuv run marimo run notebooks/\u003cnotebook_name\u003e.py\n```\n\nThis will open it locally in your browser.\n\n\n## Models\n\n### Supervised Learning\n\n| Model                       | Task                       | Notebook                                                                                                      |\n|-----------------------------|----------------------------|---------------------------------------------------------------------------------------------------------------|\n| Linear Regression           | Regression                 | [Open in Google Colab](https://colab.research.google.com/drive/1wY8SJHIF5Fctl9cdFzvVnXRgu_aDbDtf?usp=sharing) |\n| Logistic Regression         | Binary Classification      | [Open in Google Colab](https://colab.research.google.com/drive/1bg2tiVSsmC9CFJGDZ9U98Eteq-qY_HhB?usp=sharing) |\n| Locally Weighted Regression | Regression                 | [Open in Google Colab](https://colab.research.google.com/drive/18kA6eUVnjfGQxv7im5oCQ3AvLwZcAJH2?usp=sharing) |\n| Softmax Regression          | Multi-class Classification | [Open in Google Colab](https://colab.research.google.com/drive/1PY_4Zr3HiQYFJT3qNj3n8rYlOaXCAG17?usp=sharing) |\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjustanotherbyte%2Finteractive-cs229","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjustanotherbyte%2Finteractive-cs229","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjustanotherbyte%2Finteractive-cs229/lists"}