eleanor oliphant Harry Potter House Eds twitter win prizes newgen books for YA readers
Search our site
Lily and the Octopus by Steven Rowley Read the opening extract of the brand new Steven Rowley book before its publication on 05/10/2017

Machine learning books

See below for a selection of the latest books from Machine learning category. Presented with a red border are the Machine learning books that have been lovingly read and reviewed by the experts at Lovereading.

With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Machine learning books and those from many more genres to read that will keep you inspired and entertained. And it's all free!


Recently Published

An Introduction to Machine Learning by Miroslav Kubat An Introduction to Machine Learning

This textbook presents fundamental machine learning concepts in an easy to understand manner by providing practical advice, using straightforward examples, and offering engaging discussions of relevant applications.
Format: Hardback - Released: 13/09/2017

Applied Machine Learning for Data Scientists and Software Engineers Framing the First Steps Toward Successful Execution by Andrew Kelleher, Adam Kelleher Applied Machine Learning for Data Scientists and Software Engineers Framing the First Steps Toward Successful Execution
,
The typical data science task in industry starts with an ask from the business. But few data scientists have been taught what to do with that ask. This book shows them how to assess it in the context of the...
Format: Paperback - Released: 08/09/2017

Thinking as Computation A First Course by Hector J. Levesque Thinking as Computation A First Course

This book guides students through an exploration of the idea that thinking might be understood as a form of computation. Students make the connection between thinking and computing by learning to write computer programs for a variety of tasks that...
Format: Paperback - Released: 08/09/2017

Artificial Intelligence for Marketing Practical Applications by Jim Sterne Artificial Intelligence for Marketing Practical Applications

A straightforward, non-technical guide to the next major marketing tool Artificial Intelligence for Marketing presents a tightly-focused introduction to machine learning, written specifically for marketing professionals.
Format: Hardback - Released: 21/08/2017

Machine Learning and Data Mining in Pattern Recognition 13th International Conference, MLDM 2017, New York, NY, USA, July 15-20, 2017, Proceedings by Petra Perner Machine Learning and Data Mining in Pattern Recognition 13th International Conference, MLDM 2017, New York, NY, USA, July 15-20, 2017, Proceedings

This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2017, held in New York, NY, USA in July/August 2017.The 31 full papers presented in this book were carefully...
Format: Paperback - Released: 04/08/2017

R Deep Learning Cookbook by Dr. PKS Prakash, Achyutuni Sri Krishna Rao R Deep Learning Cookbook
,
Powerful, independent recipes to build deep learning models in different application areas using R libraries About This Book * Master intricacies of R deep learning packages such as mxnet & tensorflow * Learn application on deep learning in different domains...
Format: Paperback - Released: 31/07/2017

Mastering Machine Learning with scikit-learn - by Gavin Hackeling Mastering Machine Learning with scikit-learn -

Use scikit-learn to apply machine learning to real-world problems About This Book * Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks * Learn how to build and evaluate performance...
Format: Paperback - Released: 24/07/2017

Machine Learning for OpenCV by Michael Beyeler Machine Learning for OpenCV

Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide. About This Book * Load, store, edit, and visualize data using OpenCV and Python * Grasp the fundamental concepts of classification, regression, and clustering...
Format: Paperback - Released: 14/07/2017

Coming Soon

Elements of Causal Inference Foundations and Learning Algorithms by Bernhard Scholkopf, Jonas Peters, Dominik Janzing Elements of Causal Inference Foundations and Learning Algorithms
, ,
The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining...
Format: Hardback - Released: 01/10/2017

Theoretical Foundation of Data Science by Theoretical Foundation of Data Science

Theoretic Foundation of Predictive Data Analytics presents the latest in data science, an area that is penetrating into virtually every discipline of science, engineering, and medicine, and is a fast evolving field. Practitioners, researchers, and graduate students often have difficulty...
Format: Paperback - Released: 01/10/2017

Machine Learning A Constraint-Based Approach by Marco (Department of Information Engineering and Mathematics, University of Siena, Italy) Gori Machine Learning A Constraint-Based Approach
, ,
Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines. The book presents the information...
Format: Paperback - Released: 01/11/2017

Other books in this genre

Fundamentals of Deep Learning Designing Next-Generation Machine Intelligence Algorithms by Nikhil Buduma, Nicholas Locascio Fundamentals of Deep Learning Designing Next-Generation Machine Intelligence Algorithms
,
With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts...
Format: Paperback - Released: 25/06/2017

Cloud Computing for Machine Learning and Cognitive Applications by Kai (Professor of Electrical Engineering and Computer Science, University of Southern California) Hwang Cloud Computing for Machine Learning and Cognitive Applications
,
This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based technologies for data storage, transmission and mashup, and AI techniques to analyze this data....
Format: Hardback - Released: 16/06/2017

Human and Machine Hearing Extracting Meaning from Sound by Richard F. Lyon Human and Machine Hearing Extracting Meaning from Sound

This book describes how human hearing works and how to build machines that analyze sounds in the same way that people do.
Format: Hardback - Released: 02/05/2017

Apache Spark 2.x for Java Developers by Sourav Gulati, Sourav Gulati Apache Spark 2.x for Java Developers
,
Unleash the data processing and analytics capability of Apache Spark with the language of choice-Java About This Book * Perform Big Data processing with Spark-without having to learn Scala! * Use the Spark Java API to implement efficient enterprise-grade applications...
Format: Paperback - Released: 28/04/2017

Deep Learning with Keras by Antonio Gulli, Sujit Pal Deep Learning with Keras
,
Get to grips with the basics of Keras to implement fast and efficient deep-learning models About This Book * Implement various deep-learning algorithms in Keras and see how deep-learning can be used in games * See how various deep-learning models...
Format: Paperback - Released: 26/04/2017

Effective Amazon Machine Learning by Alexis Perrier Effective Amazon Machine Learning

Learn to leverage Amazon's powerful platform for your predictive analytics needs About This Book * Create great machine learning models that combine the power of algorithms with interactive tools without worrying about the underlying complexity * Learn the What's next?...
Format: Paperback - Released: 25/04/2017

Mastering Machine Learning with R by Cory Lesmeister Mastering Machine Learning with R

Master machine learning techniques with R to deliver insights in complex projects About This Book * Understand and apply machine learning methods using an extensive set of R packages such as XGBOOST * Understand the benefits and potential pitfalls of...
Format: Paperback - Released: 24/04/2017

Reasoning about Uncertainty by Joseph Y. Halpern Reasoning about Uncertainty

In order to deal with uncertainty intelligently, we need to be able to represent it and reason about it. In this book, Joseph Halpern examines formal ways of representing uncertainty and considers various logics for reasoning about it. While the...
Format: Paperback - Released: 07/04/2017

Machine Learning with Tensorflow by Nishant Shukla Machine Learning with Tensorflow

DESCRIPTION Being able to make near-real-time decisions is becoming increasingly crucial. To succeed, we need machine learning systems that can turn massive amounts of data into valuable insights. But when you're just starting out in the data science field, how...
Format: Paperback - Released: 28/03/2017

Hands on Machine Learning with Scikit-Learn and Tensorflow Concepts, Tools, and Techniques for Building Intelligent Systems by Aurelien Geron Hands on Machine Learning with Scikit-Learn and Tensorflow Concepts, Tools, and Techniques for Building Intelligent Systems

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data....
Format: Paperback - Released: 24/03/2017

Registered users have access to unique site features

Register now