Data Science books

manning.com / catalog / Data Science
Dan Van Boxel , 2017
Andrew G. Psaltis , 2017
(4)
Brian Godsey , 2017
(1)
Petar Zečević and Marko Bonaći , 2016
Henrik Brink, Joseph W. Richards, and Mark Fetherolf
Foreword by Beau Cronin
, 2016
Douglas G. McIlwraith, Haralambos Marmanis, and Dmitry Babenko
Foreword by Yike Guo
, 2016
(1)
Michael S. Malak and Robin East , 2016
Davy Cielen, Arno D. B. Meysman, and Mohamed Ali , 2016
Avi Pfeffer
Foreword by Stuart Russell
, 2016
(4)
Philipp K. Janert , 2016
(2)
Robert I. Kabacoff , 2015
(1)
Nathan Marz and James Warren , 2015
Sean T. Allen, Matthew Jankowski, and Peter Pathirana
Foreword by Andrew Montalenti
, 2015
(3)
Nina Zumel and John Mount
Foreword by Jim Porzak
, 2014
David Wood, Marsha Zaidman, Luke Ruth, and Michael Hausenblas
Foreword by Tim Berners-Lee
, 2013
(1)
William Back, Nicholas Goodman, and Julian Hyde , 2013
(2)
Grant S. Ingersoll, Thomas S. Morton, and Andrew L. Farris
Foreword by Liz Liddy
, 2012
Robert I. Kabacoff , 2011
Chris A. Mattmann and Jukka L. Zitting , 2011
Sean Owen, Robin Anil, Ted Dunning, and Ellen Friedman , 2011
(1)
Michael McCandless, Erik Hatcher, and Otis Gospodnetić , 2010
Opher Etzion and Peter Niblett , 2010
(2)
Philipp K. Janert , 2009
Erik Hatcher and Otis Gospodnetic , 2004
Chuck Lam , 2010
Satnam Alag , 2008
1 12 13
Dive into the cutting-edge world of data science with our comprehensive collection. From foundational machine learning concepts to advanced AI applications, discover how to harness the power of data for real-world solutions. Learn essential techniques in deep learning, natural language processing, and generative AI, while mastering practical skills in data engineering, analysis, and visualization. Explore modern approaches to causal inference, outlier detection, and streaming data processing, alongside emerging technologies like knowledge graphs and large language models. Whether you're building AI-powered applications, implementing data pipelines, or developing sophisticated analytics solutions, find the expertise you need to transform raw data into actionable insights. For a more detailed breakdown, take a look at the following categories: AI books Big Data books Apache Spark books Big Data Processing books Graph Analysis books Stream Processing books Streaming Data Processing books Data Analysis books Data Analysis books Data Analysis and Business Intelligence books Data Manipulation and Analysis books Data Presentations and Visualizations books Feature Engineering books Optimization and Experimentation books Data Engineering books Data Engineering books Data Management and Organization books Data Science Infrastructure books Data Science with Python books Data Visualization books Recommender Systems books Software Engineering in Data Science books Deep Learning books Deep Learning books Generative AI books Machine Learning books Computer Vision books Distributed Machine Learning books Interpretable Machine Learning books Knowledge Graphs books Machine Learning books Machine Learning Algorithms books Natural Language Processing books Natural Language Processing (NLP) books Quantum Computing/Programming books Miscellaneous books