Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
- machine-learning
- models
- ui
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Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
Data Apps & Dashboards for Python. No JavaScript Required.
Fast and Accurate ML in 3 Lines of Code
Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.
An open source extension that connects AI agents to computational notebooks in JupyterLab.
Visualize and compare datasets, target values and associations, with one line of code.
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
Lightweight and extensible compatibility layer between dataframe libraries!
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
No-code in the front, Python in the back. An open-source framework for creating data apps.
Cloud-native genomic dataframes and batch computing
[CONTRIBUTORS WELCOME] Generalized Additive Models in Python
Python DataFrames as Interactive DataTables
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
Rich-powered CLI that breaks each HTTP request into DNS, connect, TLS, wait, and transfer phases with waterfall timelines, compact summaries, or metrics-only output.
Interactive network visualization in Python and Dash, powered by Cytoscape.js
Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!
An elegant Python interface for visualization on the web platform to interactively generate insights into multidimensional images, point sets, and geometry.
Main yt repository
A py.test plugin to validate Jupyter notebooks
[IROS 2020] se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains
Multiple Pairwise Comparisons (Post Hoc) Tests in Python
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.