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Streamlit — A faster way to build and share data apps.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
:memo: An awesome Data Science repository to learn and apply for real world problems.
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
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.
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Next generation of automated data exploratory analysis and visualization platform.
Java dataframe and visualization library
🛠 All-in-one web-based IDE specialized for machine learning and data science.
Visualize and compare datasets, target values and associations, with one line of code.
Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/
Materials for GWU DNSC 6279 and DNSC 6290.
Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
Go's answer to pandas + scikit-learn: a batteries-included data analysis library with dataframes, statistics, machine learning, quant, and GPU acceleration. Run Python with seamless two-way variable sharing, or explore data straight from the Insyra CLI.
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.