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Stars
PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics
davidwhiting / openai-cookbook
Forked from openai/openai-cookbookExamples and guides for using the OpenAI API
davidwhiting / mlx-examples
Forked from ml-explore/mlx-examplesExamples in the MLX framework
davidwhiting / llama_index
Forked from run-llama/llama_indexLlamaIndex is a data framework for your LLM applications
davidwhiting / Verba
Forked from weaviate/VerbaRetrieval Augmented Generation (RAG) chatbot powered by Weaviate
davidwhiting / wave
Forked from h2oai/waveRealtime Web Apps and Dashboards for Python and R
davidwhiting / microblog
Forked from miguelgrinberg/microblogA microblogging web application written in Python and Flask that I developed as part of my Flask Mega-Tutorial series.
Recipes for Driverless AI
davidwhiting / shap
Forked from shap/shapA unified approach to explain the output of any machine learning model.
davidwhiting / waveton
Forked from vopani/waveton100 applications built with H2O Wave
Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/
H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://docs.h2o.ai/h2o-llmstudio/
Realtime Web Apps and Dashboards for Python and R
davidwhiting / pydata-book
Forked from wesm/pydata-bookMaterials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
davidwhiting / interpretable_machine_learning_with_python
Forked from jphall663/interpretable_machine_learning_with_pythonPractical techniques for training interpretable ML models, explaining ML models, and debugging ML models.
davidwhiting / awesome-machine-learning-interpretability
Forked from jphall663/awesome-machine-learning-interpretabilityA curated list of awesome machine learning interpretability resources.