GitHub is where people build software. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects.

Collection of data science projects in Python. Contribute to veb-101/Data-Science-Projects development by creating an account on GitHub.

A collection of data analysis and visualization projects designed to uncover insights from diverse datasets. These projects include analyses on COVID-19 trends, stock trading patterns, housing market prices, IoT data, and more, showcasing the power of data-driven storytelling ...

AWESOME DATA SCIENCE Contributions are welcome - see CONTRIBUTING.md. An open-source Data Science repository to learn and apply concepts toward solving real- world problems. This is a shortcut path to start studying Data Science. Just follow the steps to answer the questions, "What is Data Science, and what should I study to learn Data Science?"

GitHub is where people build software. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects.

Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge from structured and unstructured data. Data scientists perform data analysis and preparation, and their findings inform high-level decisions in many organizations.

GitHub is where people build software. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects.

10 Weeks, 20 Lessons, Data Science for All! Contribute to microsoft/Data-Science-For-Beginners development by creating an account on GitHub.

Cookiecutter Data Science A logical, reasonably standardized but flexible project structure for doing and sharing data science work. Cookiecutter Data Science (CCDS) is a tool for setting up a data science project template that incorporates best practices. To learn more about CCDS's philosophy, visit the project homepage.

DeepAnalyze is the first agentic LLM for autonomous data science. It can autonomously complete a wide range of data-centric tasks without human intervention, supporting: 🛠 Entire data science pipeline: Automatically perform any data science tasks such as data preparation, analysis, modeling, visualization, and report generation.