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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 collection of infrastructure and tools for research in neural network interpretability.
A unified, comprehensive and efficient recommendation library
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
A light-weight, flexible, and expressive statistical data testing library
Performance analysis of predictive (alpha) stock factors
Missing data visualization module for Python.
N-D labeled arrays and datasets in Python
Scalable and user friendly neural :brain: forecasting algorithms.
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
A library of reinforcement learning components and agents
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
A highly efficient implementation of Gaussian Processes in PyTorch
a library for audio and music analysis
A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.)
Vizro is a low-code toolkit for building high-quality data visualization apps.
Plotting library for IPython/Jupyter notebooks
Python library that makes it easy for data scientists to create charts.
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
C++ library for audio and music analysis, description and synthesis, including Python bindings
Models, data loaders and abstractions for language processing, powered by PyTorch
Fast, flexible and easy to use probabilistic modelling in Python.
Bayesian optimization in PyTorch
Generate embeddings from large-scale graph-structured data.
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
Datetimes for Humans™
Accelerated deep learning R&D
Tensorforce: a TensorFlow library for applied reinforcement learning
Python Toolkit for Causal and Probabilistic Reasoning
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
NumPy and Pandas interface to Big Data
The machine learning toolkit for time series analysis in Python
TensorFlow Reinforcement Learning
Visualize and compare datasets, target values and associations, with one line of code.
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
High performance datastore for time series and tick data
Shōgun
StellarGraph - Machine Learning on Graphs
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
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/
With Holoviews, your data visualizes itself.
NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
Data manipulation and transformation for audio signal processing, powered by PyTorch
Pandas integration with sklearn
Sequential model-based optimization with a `scipy.optimize` interface
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.
POT : Python Optimal Transport
Neural Network Libraries
Learning to Rank in TensorFlow