>_QGDS

Reference Books

The best Data Science books, hand-picked for every level — from your first Python script to production ML systems.

Python for Data Analysis
Beginner

Python for Data Analysis

Wes McKinney (3rd Edition, O'Reilly)

The definitive guide to pandas, NumPy, and the modern Python data stack — written by the creator of pandas himself.

$42.90View on Amazon
Hands-On Machine Learning
Intermediate

Hands-On Machine Learning

Aurélien Géron (3rd Edition, O'Reilly)

From linear regression to deep neural nets with Scikit-Learn, Keras and TensorFlow. The most recommended ML book of the decade.

$59.90View on Amazon
The Elements of Statistical Learning
Advanced

The Elements of Statistical Learning

Hastie, Tibshirani & Friedman

The mathematical backbone behind every modern ML algorithm. Dense, rigorous, and essential for anyone going deep.

$74.00View on Amazon
Storytelling with Data
Beginner

Storytelling with Data

Cole Nussbaumer Knaflic

Numbers don't speak for themselves. Learn to design charts and narratives that actually move stakeholders to action.

$36.50View on Amazon
Designing Data-Intensive Applications
Advanced

Designing Data-Intensive Applications

Martin Kleppmann

The systems thinking behind every reliable data platform. A must-read once you start shipping pipelines to production.

$54.90View on Amazon
Practical Statistics for Data Scientists
Intermediate

Practical Statistics for Data Scientists

Bruce, Bruce & Gedeck (2nd Edition)

The statistics you forgot from college, rewritten for people who write code. Short, direct and full of working examples.

$45.00View on Amazon