🚀 Free & Relevant Books for Data Science (2025) 📚

Want to sharpen your Python & DS skills without outdated material? Here are some modern, still-relevant free books 👇

1️⃣ Python Data Science Handbook – Jake VanderPlas
🔗 https://jakevdp.github.io/PythonDataScienceHandbook
Core libs: NumPy, Pandas, Matplotlib, Scikit-Learn. Updated + interactive notebooks.

2️⃣ Python for Data Analysis (3rd Ed.) – Wes McKinney
🔗 https://github.com/wesm/pydata-book
By the creator of Pandas. Modern data wrangling & cleaning.

3️⃣ Dive into Deep Learning (D2L.ai)
🔗 https://d2l.ai
Hands-on deep learning with PyTorch & TensorFlow. University-level, interactive.

4️⃣ Minimalist Data Wrangling with Python (2023) – Marek Gagolewski
🔗 https://arxiv.org/abs/2211.04630
Practical workflows for real-world messy data.


5️⃣ Machine Learning with PyTorch & Scikit-Learn – Raschka et al.
🔗 https://github.com/rasbt/machine-learning-book
End-to-end ML with clean, modern Python code.

✨ Start with VanderPlas & McKinney for core skills, then move to Raschka/D2L for ML.