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1. gpt-all-local gpt-all-local Public

   A "chat with your data" example: using a large language models (LLM) to interact with our own (local) data. Everything is local: the embedding model, the LLM, the vector database. This is an exampl…

   Python 27 5

2. llm-github-issues llm-github-issues Public

   Summarizing with LLMs: Using an LLM to understand GitHub issues without reading each post in detail.

   Python 13

3. writing-good-jupyter-notebooks writing-good-jupyter-notebooks Public

   Writing good Jupyter notebooks: logically organized, clearly documented decisions and assumptions, easy-to-understand code, flexible (easy to modify) code, resilient (hard to break) code

   Jupyter Notebook 3

4. ieee-icmla-2019-data-science-tutorial ieee-icmla-2019-data-science-tutorial Public

   IEEE ICMLA 2019 Data Science Tutorial - using data to answer questions

   Jupyter Notebook 9 4

5. cap5768-introduction-to-data-science cap5768-introduction-to-data-science Public

   Data science with Pandas and NumPy: EDA, binning, distribution functions, simulations, regression analysis

   Jupyter Notebook 11

6. machine-learning-but-not-understanding machine-learning-but-not-understanding Public

   Are machines "learning" anything? This repository explores some of the concepts from the book "Artificial Intelligence, a guide for thinking humans", by Melanie Mitchell.

   Jupyter Notebook