The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
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The most powerful local music generation model that outperforms almost all commercial alternatives, supporting Mac, AMD, Intel, and CUDA devices.
- text2music
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen3.6, GPT-OSS, Llama, and more!
Run 35B MoE models in ~2.5 GB of RAM. Weights stream from SSD; a trained router predicts loads a step ahead. Mac, iPhone, Android, Windows supported
DEPRECATED: Like diff but for PostgreSQL schemas
- developer-tools
- developer-experience
- postgresql
- schema-changes
Genetic Programming in Python, with a scikit-learn inspired API
- genetic-programming
- machine-learning
- python
- scikit-learn
Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
- diffusion-models
- docking
- binding
- computational-biology
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
- forecasting
- scikit-learn
- machine-learning
- python
CodeAgent is an open-source coding agent that lives in your terminal. It understands your repository, plans multi-step changes, writes and edits files, runs commands and tests, and iterates until the task is done — all with a transparent, extensible tool loop.
Train and Deploy an ML REST API to predict crypto prices, in 10 steps
TranslatedAgent Skill step-by-step governance system: the program guarantees that the Agent does not skip steps (step-gate Rust gating + delivery gate + chain governance)
TranslatedOntiCards is an enterprise-oriented AI Data Hub that offers one-stop capabilities around business databases: data source connection, metadata understanding, natural language query, cross-source fusion, data quality inspection, query auditing, data asset management, and more
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
- pipeline
- pipeline-framework
- machine-learning
- deep-learning
SolarRenderer: Few-Step Generative Reference Rendering
A python 3 library to connect various motor systems to a Raspberry pi single board computer
- raspberry-pi
- motor
- servo
- 28byj-48
One-Step APK Decompilation With Multiple Backends
TranslatedMCP desktop companion for AI agent status, usage tracking, and everyday tools. Anything Universe · Desktop companion and entry point to everyday tools.
[Tech Report] Simplifying and Improving On-Policy Distillation for Few-step Diffusion
- diffusion
- distillation
- few-step-generation
TranslatedBuild GPT-2 from scratch in PyTorch, step by step
- attention
- chinese
- deep-learning
- from-scratch
A low-glare Dracula-inspired VS Code theme with measured WCAG AA contrast, muted UI accents, and six-step bracket-depth highlighting.
Build and deploy a serverless data pipeline on AWS with no effort.
- aws-cdk
- data-pipeline
- stepfunctions
- glue
Selenium webdriver step library for use with the behave BDD testing framework
- selenium-webdriver
- webdriverio
- behave
- bdd
The elegance of Airflow + the power of AWS
- aws
- orchestration
- step-functions
Micropython code to drive stepper motors via ULN2003