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Awesome List
Probably the best curated list of data science software in Python.
GitHub stars and default-branch commits for krzjoa/awesome-python-data-science.
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A game theoretic approach to explain the output of any machine learning model.
Always know what to expect from your data.
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
Plotting library for IPython/Jupyter notebooks
Bayesian optimization in PyTorch
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/
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
ML powered analytics engine for outlier detection and root cause analysis.