Intentional is an open-source framework to build reliable LLM chatbots that actually talk and behave as you expect.

LLMFlows - Simple, Explicit and Transparent LLM Apps

Python package for conformal prediction

LLM prompt language based on Jinja. Banks provides tools and functions to build prompts text and chat messages from generic blueprints. It allows attaching metadata to prompts to ease their managem…

Awesome-LLM: a curated list of Large Language Model

Distribute and run LLMs with a single file.

🐢 Open-Source Evaluation & Testing for AI & LLM systems

Compendium of free ML reading resources

🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 | 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟𝗘 & 𝗠𝗟𝗢𝗽𝘀 for free by designing, building and deploying an end-to-end ML batch system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 2.5 𝘩𝘰𝘶𝘳𝘴 𝘰𝘧 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 & 𝘷𝘪𝘥𝘦𝘰 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴

A library for efficient similarity search and clustering of dense vectors.

Delta Acceptance Testing

Delta Lake helper methods in PySpark

A light-weight, flexible, and expressive statistical data testing library

🧱 Databricks CLI eXtensions - aka dbx is a CLI tool for development and advanced Databricks workflows management.

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…

A debugging and profiling tool that can trace and visualize python code execution

Open World Holidays Framework

implementation of recombinator-k-means

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course

Perform data science on data that remains in someone else's server

Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts

🤹‍♀ Animations of tidyverse verbs using R, the tidyverse, and gganimate

Pandas ExtensionDType/Array backed by Apache Arrow

A C++ platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)

A short guide on features of Python 3 with examples

Numpy-compatible bit generators and add some random variate distributions missing from NumPy.

Python bindings for the fast integer compression library FastPFor.