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The Woman in the Window by A. J. Finn Read the opening extract of the brand new A. J. Finn book before its publication on 22/01/2018

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

Machine Learning for the Quantified Self On the Art of Learning from Sensory Data by Mark Hoogendoorn, Burkhardt Funk Machine Learning for the Quantified Self On the Art of Learning from Sensory Data
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This book explains the complete loop to effectively use self-tracking data for machine learning. While it focuses on self-tracking data, the techniques explained are also applicable to sensory data in general, making it useful for a wider audience.
Format: Hardback - Released: 20/11/2017

Elements of Causal Inference Foundations and Learning Algorithms by Bernhard Scholkopf, Jonas Peters, Dominik Janzing Elements of Causal Inference Foundations and Learning Algorithms
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A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.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...
Format: Hardback - Released: 17/11/2017

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
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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: 15/11/2017

Machine Learning and Cognition in Enterprises Business Intelligence Transformed by Rohit Kumar Machine Learning and Cognition in Enterprises Business Intelligence Transformed

Learn about the emergence and evolution of IT in the enterprise, see how machine learning is transforming business intelligence, and discover various cognitive artificial intelligence solutions that complement and extend machine learning. In this book, author Rohit Kumar explores the...
Format: Paperback - Released: 28/10/2017

Advances in Soft Computing and Machine Learning in Image Processing by Aboul (Cairo University Egypt) Ella Hassanien Advances in Soft Computing and Machine Learning in Image Processing

It can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence, and is a valuable resource for researchers in the evolutionary computation, artificial intelligence and image processing communities.
Format: Hardback - Released: 13/10/2017

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

Python Machine Learning - by Sebastian Raschka, Vahid Mirjalili Python Machine Learning -
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Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. About This Book * Second edition of the bestselling book on Machine Learning * A practical approach to key frameworks in...
Format: Paperback - Released: 20/09/2017

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: 08/09/2017

Coming Soon

Data Stream Mining with Practical Examples in MOA by Albert (Associate Professor, Telecom ParisTech) Bifet, Ricard (Professor, Universitat Politecnica de Catalunya, Campus Gavalda Data Stream Mining with Practical Examples in MOA
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A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework.Today many information sources -- including sensor networks, financial markets, social networks, and healthcare monitoring --...
Format: Hardback - Released: 02/02/2018

Other books in this genre

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
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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

Machine Learning in Medical Imaging 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings by Qian Wang Machine Learning in Medical Imaging 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings

This book constitutes the refereed proceedings of the 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The main aim of this workshop is...
Format: Paperback - Released: 07/09/2017

Advances in Neural Computation, Machine Learning, and Cognitive Research Selected Papers from the XIX International Conference on Neuroinformatics, October 2-6, 2017, Moscow, Russia by Boris Kryzhanovsky Advances in Neural Computation, Machine Learning, and Cognitive Research Selected Papers from the XIX International Conference on Neuroinformatics, October 2-6, 2017, Moscow, Russia

This book describes new theories and applications of artificial neural networks, with a special focus on neural computation, cognitive science and machine learning.
Format: Hardback - Released: 29/08/2017

Learning TensorFlow by Tom Hope, Yehezkel S. Resheff, Itay Lieder Learning TensorFlow
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This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics.
Format: Paperback - Released: 25/08/2017

Machine Learning and Knowledge Extraction First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 - September 1, 2017, Proceedings by Andreas Holzinger Machine Learning and Knowledge Extraction First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 - September 1, 2017, Proceedings

This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2017, held in Reggio, Italy, in August/September 2017.The 24 revised full papers presented were carefully...
Format: Paperback - Released: 24/08/2017

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

Students explore the idea that thinking is a form of computation by learning to write simple computer programs for tasks that require thought. This book guides students through an exploration of the idea that thinking might be understood as a...
Format: Paperback - Released: 11/08/2017

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: 04/08/2017

R Deep Learning Cookbook by Dr. PKS Prakash, Achyutuni Sri Krishna Rao R Deep Learning Cookbook
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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

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: 04/07/2017

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