Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.

Self-Adapting Language Models

PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics

Examples and guides for using the OpenAI API

Examples in the MLX framework

LlamaIndex is a data framework for your LLM applications

Retrieval Augmented Generation (RAG) chatbot powered by Weaviate

Realtime Web Apps and Dashboards for Python and R

Examples in the MLX framework

MLX: An array framework for Apple silicon

Use emojione Emojis in LaTeX

A microblogging web application written in Python and Flask that I developed as part of my Flask Mega-Tutorial series.

Recipes for Driverless AI

A unified approach to explain the output of any machine learning model.

100 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

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

Practical techniques for training interpretable ML models, explaining ML models, and debugging ML models.

A curated list of awesome machine learning interpretability resources.