Books
The best books on Data Science, Big Data, Data Mining, Machine Learning, Python, R, SQL, NoSQL and more. Sorted by popularity.
4.0 (33 Ratings)OpenIntro Statistics
Probability is optional, inference is key, and we feature real data whenever possible. Files for the entire book are freely available at openintro.org.
4.1 (30 Ratings)Data-Intensive Text Processing with MapReduce
MapReduce [45] is a programming model for expressing distributed computations on massive amounts of data and an execution framework for large-scale data processing on clusters of commodity servers. It was originally developed by Google...
4.4 (25 Ratings)Mining of Massive Datasets
Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond.
4.2 (24 Ratings)Elementary Applied Topology
This text gives a brisk and engaging introduction to the mathematics behind the recently established field of Applied Topology.
4.1 (24 Ratings)Design and Analysis of Experiments, 8th Edition
This book helps senior and graduate students in engineering, business, and statistics-as well as working practitioners-to design and analyze experiments for improving the quality, efficiency and performance of working systems.
4.1 (23 Ratings)A Byte of Python
‘A Byte of Python’ is a free book on programming using the Python language. It serves as a tutorial or guide to the Python language for a beginner audience. If all you know about computers is how to save text files, then this is the book for you.
3.6 (23 Ratings)Artificial Intelligence: Foundations of Computational Agents
This is a textbook aimed at junior to senior undergraduate students and first-year graduate students. It presents artificial intelligence (AI) using a coherent framework to study the design of intelligent computational agents.
3.6 (22 Ratings)Graph Databases
Get started with O'Reilly's Graph Databases and discover how graph databases can help you manage and query highly connected data.
4.3 (15 Ratings)Data Mining and Analysis: Fundamental Concepts and Algorithms
The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification. The book lays the basic foundations of these tasks, and also covers many more cutting-edge data mining topics.
3.7 (15 Ratings)The Art of Data Science
This book describes the process of analyzing data. The authors have extensive experience both managing data analysts and conducting their own data analyses, and this book is a distillation of their experience...