Data Science
Showing 36 of 625 projects
A Python toolkit for causal and probabilistic reasoning using graphical models like Bayesian Networks and Structural Equation Models.
An Automated Machine Learning Python package for tabular data with feature engineering, hyperparameter tuning, explanations, and automatic documentation.
A Jupyter kernel for C++ that enables interactive computing with cling interpreter and xeus protocol.
A Python library that makes machine learning models interpretable and transparent through user-friendly visualizations and a web application.
A visual roadmap and keyword mind map for students learning Natural Language Processing, from basics to SOTA models.
An engine and API for running .NET and other languages interactively in notebooks, REPLs, and embedded coding experiences.
A Python machine learning toolkit for time series analysis with scikit-learn compatible API.
A Python library for automated exploratory data analysis (EDA) with high-density visualizations and target analysis in two lines of code.
A high-performance, easy-to-use, and scalable machine learning package for linear models, factorization machines, and field-aware factorization machines.
A unified and efficient machine learning toolbox with C++ core and multi-language interfaces, developed since 1999.
An open-source, AI-first data notebook that extends Jupyter with a sleek UI, reactive execution, and native data integrations.
Fast tool for comparing datasets within or across SQL databases to identify differences.
An extensible open-source toolkit for detecting, mitigating, and explaining bias in machine learning datasets and models.
A library for debugging/inspecting machine learning classifiers and explaining their predictions
A curated collection of hands-on data science project ideas and resources for learning machine learning and AI concepts.
Docker image providing the Python environment used by Kaggle Notebooks for data science competitions.
A comprehensive collection of machine learning algorithms and mathematical utilities implemented in JavaScript for browser and Node.js.
A Python package that automatically accelerates pandas and Modin DataFrame apply operations by choosing the fastest available method.
A Python library for defining portable, modular, and testable data transformation DAGs with built-in lineage and metadata.
A lightweight Python library for creating portable, expressive, and testable data transformation DAGs with built-in lineage and metadata.
A pure Python library for survival analysis, modeling time-to-event data with censoring.
A collection of beginner-friendly TensorFlow tutorials using Jupyter Notebook, covering deep learning fundamentals and practical applications.
A Python library for loading, shaping, embedding, and exploring large graphs with GPU-accelerated visualization and analytics.
HyperLearn provides 2-2000x faster machine learning algorithms with 50% less memory usage, optimized for all hardware.
A Python tutorial and cookbook for implementing Bayesian modeling techniques using PyMC3.
A Jupyter Notebook kernel and interactive REPL for Go (golang) that enables interactive programming and data analysis.
An intuitive Python library that adds single-line plotting functions for scikit-learn and other machine learning objects.
A machine learning framework for developing high-frequency trading strategies using full orderbook tick data.
A concise mathematical reference covering essential topics in probability theory and statistics.
A modern R console with multiline editing, syntax highlighting, and improved REPL features.
A Python library for feature engineering and selection with scikit-learn compatible transformers.
An open-source Python library for low-code data preparation, offering fast EDA, data cleaning, and collection from APIs and databases.
A collection of GPU-accelerated graph analytics libraries for creating, manipulating, and executing scalable graph algorithms.
A curated list of libraries, tutorials, and resources for implementing machine learning in the Ruby programming language.
A curated list of awesome libraries, data sources, tutorials, and resources for machine learning using the Ruby programming language.
A curated collection of R tutorials, packages, and resources for Data Science, NLP, and Machine Learning.
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