Oreilly Essential Math for Data Science Paperback

**Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics** by Thomas Nield is a practical guide to the mathematical concepts needed for data science and machine learning.

The book explains probability, statistics, hypothesis testing, linear algebra, calculus, and machine learning in clear and accessible language. It uses practical Python examples and libraries such as SymPy, NumPy, and scikit-learn to connect mathematical concepts with real-world data science applications.

Readers learn how to understand probability, perform statistical analysis, work with vectors and matrices, perform calculus calculations in Python, and apply mathematics to linear regression, logistic regression, and neural networks.

This book is ideal for aspiring data scientists, data analysts, machine learning professionals, programmers, and students who want to build a strong mathematical foundation for data science.

**Author:** Thomas Nield **Publisher:** O'Reilly Media **Format:** Paperback **Publication:** 2022 **ISBN:** 9781098102937 **Pages:** 349–350