Streamlit — A faster way to build and share data apps.
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Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
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.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Visual tracking library based on PyTorch.
Visualize and compare datasets, target values and associations, with one line of code.
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
An intuitive library to add plotting functionality to scikit-learn objects.
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
moDel Agnostic Language for Exploration and eXplanation
🎆 A visualization of the CapsNet layers to better understand how it works
MCP server for spatial transcriptomics analysis through natural language interfaces.
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.