Data Science EBooks alternatives for AI agents.

Jupyter extensions that help you write code faster: Context aware AI Chat, Autocomplete, and Spreadsheet

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

Visualize and compare datasets, target values and associations, with one line of code.

Open-source AI-powered data science platform.

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/

Multi-class confusion matrix library in Python

The fastest business intelligence tool for humans and agents.

I am sharing my Journey of 66DaysofData into Data Analytics by participating in Ken Jee's #66daysofdata challenge

10 Weeks, 20 Lessons, Data Science for All!

Streamlit — A faster way to build and share data apps.

🕸️ Web apps in pure Python 🐍

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.

Chat with your data - AI data analysis and visualization on CSV, Postgres, MySQL, Snowflake, SQLite...

免费的AI可视化报表。一句话描述需求，AI 自动生成报表与数据大屏；同时提供类 Excel 拖拽设计器，兼容 30 余种数据源，轻松应对各类复杂报表场景——帆软、Tableau 的高性价比开源替代。

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.