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@fau-masters-collected-works-cgarbin

Christian Garbin CS master's and Ph.D. collected works

Work created during FAU's computer science master's and Ph.D. (data science, machine learning, ...)

Pinned

  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 18 1

  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 4

  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 5

  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 10

  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

Repositories

Showing 10 of 26 repositories
  • llm-github-issues Public

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

    Python 4 MIT 0 0 0 Updated Apr 21, 2024
  • 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 example of retrieval-augmented generation (RAG): we find relevant sections from our documents and pass it to the LLM as part of the prompt (see pics).

    Python 18 1 0 0 Updated Apr 21, 2024
  • cap5768-introduction-to-data-science Public

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

    Jupyter Notebook 10 MIT 0 0 0 Updated Jan 6, 2024
  • ieee-icmla-2019-data-science-tutorial Public

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

    Jupyter Notebook 9 GPL-3.0 5 0 0 Updated Jan 6, 2024
  • 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 0 0 0 Updated Jan 6, 2024
  • llm-comparison-tool Public

    A tool to compare multiple large language models (LLMs) side by side

    Python 0 MIT 1 0 0 Updated Jan 6, 2024
  • cap6776-information-retrieval Public

    Information retrieval from basic concepts (tokenization, stop word removal, stemming, TF-IDF, etc.)

    Python 0 0 0 0 Updated Nov 12, 2023
  • obfuscated-c-12-days-of-christmas Public

    Methodically "unobfuscate" the winner of the 1988 International Obfuscated C Contest entry, the incredible code that prints the "twelve days of Christmas" song.

    C 0 0 0 0 Updated Oct 9, 2023
  • decision-threshold-effect-on-accuracy Public

    What is "accuracy"? The effect of changing the decision threshold on a model's accuracy.

    Jupyter Notebook 0 0 0 0 Updated Jul 9, 2023
  • 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 0 MIT 0 0 0 Updated Jul 8, 2023

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