Python Machine Learning By Example 4th Edition

Grab attention with a clear promise: Python Machine Learning By Example, 4th Edition by Yuxi (Hayden) Liu is a hands-on roadmap for turning Python code into real-world machine learning solutions. This updated edition blends approachable explanations with practical projects, making advanced concepts accessible to developers, data scientists, and students worldwide.

Build confidence quickly with concise, example-driven chapters that demystify supervised and unsupervised learning, deep learning fundamentals, model evaluation, and deployment strategies. You’ll work through real datasets and progressively complex projects that teach best practices for preprocessing, feature engineering, model selection, and performance tuning — all using modern Python tools and libraries.

Imagine converting theory into tangible results: whether you’re building predictive models for business, exploring computer vision, or deploying scalable models to production, this book emphasizes transferable skills and reproducible workflows. It’s equally valuable for beginners seeking structured learning and experienced practitioners refreshing their toolset.

Perfect for readers across North America, Europe, Asia, Australia, and beyond, this edition reflects recent advances in the ML ecosystem while remaining practical and example-focused. Clear code examples, step-by-step explanations, and actionable tips make it an ideal companion for self-study, upskilling, or classroom use.

Ready to level up your machine learning career? Add Python Machine Learning By Example (4th Edition) by Yuxi (Hayden) Liu to your library today and start building intelligent applications with confidence.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.