1.jakevdp / PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
Ranked by Attention Score: stars gained over the last 7 complete days
33 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)
Python Data Science Handbook: full text in Jupyter Notebooks
✅(已完结)超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】
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.
The interactive graphing library for Python :sparkles:
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Instructional notebooks on music information retrieval.
Best Practices on Recommendation Systems
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment
:keyboard: A curated list of awesome tools, demos and resources to go beyond LaTeX
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch:入门与实战》)
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
JupyterLab desktop application, based on Electron.
Draw pretty maps from OpenStreetMap data! Built with osmnx +matplotlib + shapely
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
A curated list of awesome Jupyter projects, libraries and resources
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.
Debugging, monitoring and visualization for Python Machine Learning and Data Science
Tools for diffing and merging of Jupyter notebooks.
Run ruff, isort, pyupgrade, mypy, pylint, flake8, and more on Jupyter Notebooks
GoNB, a Go Notebook Kernel for Jupyter
An interactive book about the Riemann problem for hyperbolic PDEs, using Jupyter notebooks.
Dive into this repository, a comprehensive resource covering Data Structures, Algorithms, 450 DSA by Love Babbar, Striver DSA sheet, Apna College DSA Sheet, and FAANG Questions! 🚀 That's not all! We've got Technical Subjects like Operating Systems, DBMS, SQL, Computer Networks, and Object-Oriented Programming, all waiting for you.
Ready-to-run Docker images containing Jupyter applications
A collection of infrastructure and tools for research in neural network interpretability.
The Hunting ELK
Jupyter magics and kernels for working with remote Spark clusters
A filesystem-like contents manager for multiple backends in Jupyter
Big Data essentials: Hadoop, MapReduce, Spark. Explore tutorials and demos in Jupyter notebooks—most are self-contained and live, ready to run with a click.
Code repository for The Automation Ahead series, showcasing practical examples for GenAI-driven automation in investments. Each installment dives into specific tools, techniques, and use cases to help professionals assess and apply GenAI effectively.
Modern, interactive charts for Jupyter notebooks with Apache ECharts