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A Python library for audio data augmentation. Useful for making audio ML models work well in the real world, not just in the lab.

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

A Python package to assess and improve fairness of machine learning models.

Feature engineering and selection open-source Python library compatible with sklearn.

Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.

An open source library and framework for deep learning on satellite and aerial imagery.

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

TFX is an end-to-end platform for deploying production ML pipelines

A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.

Repository containing notebooks of my posts on Medium

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

ML algorithms implemented and derived from first-principles in Jupyter Notebooks and NumPy

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

🤖 A powerful, lightweight JavaScript library + interactive CLI for ChatGPT

Build LLM-powered applications in Ruby

A Julia machine learning framework

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

Genetic Programming in Python, with a scikit-learn inspired API

Natural Gradient Boosting for Probabilistic Prediction

Large-scale LLM inference engine

Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

A comprehensive guide to building RAG-based LLM applications for production.

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

Rust library for quantitative finance.

Interpretability and explainability of data and machine learning models

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

Oryx 2: Lambda architecture on Apache Spark, Apache Kafka for real-time large scale machine learning

Large-scale LLM inference engine

Reference implementations of MLPerf® training benchmarks

fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!