Data Science
Showing 36 of 624 projects
A curated list of awesome Jupyter projects, libraries, and resources for data science and interactive computing.
A curated collection of Python libraries, tutorials, and tools for data science, from data wrangling to machine learning and visualization.
Official code repository for the 'Machine Learning with TensorFlow' book with practical examples.
A library for probabilistic reasoning and statistical analysis integrated with TensorFlow and JAX.
A curated list of awesome open-source data visualization libraries, frameworks, and resources across multiple programming languages.
A curated list of awesome open-source data visualization libraries, frameworks, and resources across multiple programming languages.
A curated list of awesome open-source data visualization libraries, frameworks, and resources across multiple programming languages.
A framework for building interactive web applications directly from Python notebooks, including chats, AI agents, dashboards, and reports.
A cross-platform desktop application for JupyterLab, providing the easiest way to run Jupyter notebooks locally.
A comprehensive collection of tutorials, examples, and resources for understanding and solving machine learning and pattern classification problems.
An open-source CLI tool for implementing CI/CD workflows with a focus on MLOps, automating ML experiments and reporting.
Course materials for the Johns Hopkins Data Science Specialization on Coursera.
Course materials for the Johns Hopkins Data Science Specialization on Coursera.
A Python library that simplifies data integration between pandas and AWS services like Athena, S3, Redshift, and more.
A Python library that simplifies data integration between pandas and AWS services like Athena, S3, Redshift, and more.
A curated list of resources for constructing, analyzing, and visualizing network data across various disciplines.
A curated list of practical resources for responsible machine learning, covering interpretability, governance, safety, and ethics.
An open-source solution for continuous validation of machine learning models and data, from research to production.
Run code interactively, inspect data, and plot using Jupyter kernels directly inside the Atom text editor.
A collection of Jupyter notebooks accompanying a 10-part video series teaching machine learning with Python's scikit-learn library.
A Java dataframe and visualization library for data loading, cleaning, transformation, and analysis.
A Jupyter/IPython extension that transforms notebooks into interactive Reveal.js slideshows with live execution.
R code examples from the 'Machine Learning for Hackers' book, demonstrating practical machine learning techniques.
A Python package for interactive mapping and geospatial analysis with minimal coding in Jupyter notebooks.
An open-source platform for building, training, and monitoring large-scale deep learning applications with full lifecycle MLOps.
A Python implementation of the grammar of graphics for creating statistical visualizations.
A Python library that simplifies chart creation for data scientists with consistent data formats and smart defaults.
A Python library that simplifies chart creation for data scientists with consistent data formats and smart defaults.
The fastest way to build data pipelines with iterative development and deployment anywhere.
An easy-to-use blogging platform with enhanced support for Jupyter Notebooks, Word docs, and Markdown, powered by GitHub Actions.
A web-based IDE for machine learning and data science with pre-installed libraries and tools, deployable via Docker.
A curated list of Python software for data science, covering machine learning, deep learning, visualization, and data manipulation.
A comprehensive collection of machine learning tutorials and implementations in Python, covering algorithms from scratch to production deployment.
A debugging and visualization tool for data science, deep learning, and reinforcement learning in Jupyter Notebook.
Koalas provides the pandas DataFrame API on Apache Spark, enabling data scientists to work with big data using familiar pandas syntax.
A Python toolkit for causal and probabilistic reasoning using graphical models like Bayesian Networks and Structural Equation Models.
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