Popular GitHub Repositories for Programming Challenge

??? 60+ Implementations/tutorials of deep learning papers with side-by-side notes ?; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ? reinforcement learning (ppo, dqn), capsnet, distillation, ... ?

? The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming

A programming framework for agentic AI ? PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour

100 Days of ML Coding

aider is AI pair programming in your terminal

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

The Modular Platform (includes MAX & Mojo)

Open source AI coding agent. Designed for large projects and real world tasks.

Creative Coding: Generative Art, Data visualization, Interaction Design, Resources.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

? An exciting game of programming and Artificial Intelligence

Bayesian Modeling and Probabilistic Programming in Python

Speech-to-text, text-to-speech, speaker diarization, speech enhancement, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, x86_64 servers, websocket server/client, support 11 programming languages

Deep universal probabilistic programming with Python and PyTorch

Probabilistic language based on pattern matching and constraint propagation, 153 examples

An 11-Lesson course teaching everything you need to know about harnessing GitHub Copilot as an AI Paired Programming resource.

Python code for "Probabilistic Machine learning" book by Kevin Murphy

A language model programming library.

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Probabilistic reasoning and statistical analysis in TensorFlow