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The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
pix2tex: Using a ViT to convert images of equations into LaTeX code.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Fast and Accurate ML in 3 Lines of Code
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Scalable and user friendly neural :brain: forecasting algorithms.
Fast, flexible and easy to use probabilistic modelling in Python.
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
A collection of research papers on decision, classification and regression trees with implementations.
Feature engineering and selection open-source Python library compatible with sklearn.
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Interpretability and explainability of data and machine learning models
A deep learning toolkit for healthcare AI: EHR (MIMIC, eICU, OMOP), clinical text, signals and imaging. 30+ models, reproducible pipelines.
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
moDel Agnostic Language for Exploration and eXplanation
gradslam is an open source differentiable dense SLAM library for PyTorch
Scalable machine 🤖 learning for time series forecasting.
NFStream: a Flexible Network Data Analysis Framework.
[CONTRIBUTORS WELCOME] Generalized Additive Models in Python