Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

Interactive Tools for Machine Learning, Deep Learning and Math

An open-source tool for visual and modular block programming in python

Streamlit — A faster way to build and share data apps.

The Web framework for perfectionists with deadlines.

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

Label Studio is a multi-type data labeling and annotation tool with standardized output format

Open source platform for the machine learning lifecycle

Machine Learning Toolkit for Kubernetes

Elyra extends JupyterLab with an AI centric approach.

A hyperparameter optimization framework

Open Toolkit for Painless Object Detection

Simultaneous object detection and tracking using center points.

Reinforcement Learning in PyTorch

Neural network visualization toolkit for keras

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

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

A better notebook for Scala (and more)

📚 Parameterize, execute, and analyze notebooks

🦉 Data Versioning and ML Experiments

🛠 All-in-one web-based IDE specialized for machine learning and data science.

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

Visualizer for neural network, deep learning and machine learning models

Debugging, monitoring and visualization for Python Machine Learning and Data Science

Grid studio is a web-based application for data science with full integration of open source data science frameworks and languages.

An orchestration platform for the development, production, and observation of data assets.

Voilà turns Jupyter notebooks into standalone web applications

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,…

Fit interpretable models. Explain blackbox machine learning.

Provide an input CSV and a target field to predict, generate a model + code to run it.