Open source. Open possibilities.

An educational repository teaching supervised machine learning from first principles using Python, covering mathematical foundations and practical implementations.

Eclipse Deeplearning4J (DL4J) is a JVM-based deep learning ecosystem supporting Java, Scala, Kotlin, and more. It includes model import from Keras, TensorFlow, ONNX; ND4J for linear algebra; SameDiff for automatic differentiation; DataVec for ETL; and runs on CPU/GPU across Windows, Linux, macOS.

Made With ML is an open-source course and codebase teaching how to design, develop, deploy and iterate on production-grade machine learning applications, covering MLOps, testing, serving, CI/CD and continual learning.

Microsoft's 10-week, 20-lesson data science curriculum for beginners, with project-based lessons, quizzes, and 50+ language translations.

Official code repository for 'Build a Large Language Model (From Scratch)': step-by-step PyTorch implementation of GPT-like models, covering pretraining and finetuning with notebooks and exercises.

fastai is a deep learning library built on PyTorch that provides both high-level components for rapid productivity and low-level components for research and customization.

FiftyOne is an open-source tool for building high-quality datasets and computer vision models. It enables users to visualize, label, evaluate, and curate visual AI data.

PyTorch is an open-source machine learning library providing tensor computation with GPU acceleration and a flexible deep neural network framework based on a tape-based autograd system.

FairMind is an open‑source AI governance platform providing bias detection, fairness testing, and compliance tracking for ML, LLM, and multimodal AI models. It offers evidence‑grade evaluation, model registry, and remediation tools.

PyMC is a Python package for Bayesian statistical modeling featuring advanced MCMC and variational inference algorithms, with intuitive model specification syntax and support for complex probabilistic models.

Keras 3 is a multi-backend deep learning framework that allows users to build and train models using JAX, TensorFlow, PyTorch, or OpenVINO.

VeighNa (VeighNa Studio) is an open-source Python-based quantitative trading framework with event-driven engine, supporting domestic/international market interfaces (CTP, IB, etc.) and modules for CTA strategies, algorithm trading, risk management, and data services. The 4.0 version introduces vnpy.alpha module for AI-powered multi-factor machine learning strategy development.

A tiny GPT language model (~540M parameters) designed to be trained from scratch on consumer laptop hardware, with pretraining on Fineweb-edu and chat finetuning capabilities.

Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch, supporting universal probabilistic models and automated inference.

Free, open-source AI engineering curriculum from first principles: 523 lessons in 20 phases (~342 hours), with math-to-production coverage in Python, TypeScript, Rust, and Julia. Every lesson ships a reusable prompt, skill, agent, or MCP server; includes an installable AI tutor and Claude certification prep.

NLTK is a comprehensive suite of open-source Python modules, datasets, and tutorials designed to support research and development in Natural Language Processing.

A collection of machine learning and deep learning code examples and tutorials accompanying online courses. Covers topics from linear regression to reinforcement learning, NLP, computer vision, and generative AI.

Defense-only fraud detection for cross-merchant identity reuse. Sentinel builds an identity link graph across merchants, scores payment events deterministically with explainable verdicts, and provides an analyst console, audit trail, and measured precision, recall, and false-positive cost in rupees.

Microsoft's free 12-week, 26-lesson curriculum for learning classic machine learning with Scikit-learn. Includes quizzes, hands-on projects, assignments, Python and R lessons, and multi-language translations.

iFixAi is an independent auditing tool for AI agents that evaluates whether an agent adheres to business KPIs and organizational structures through a structured scoring system.