Machine Learning books

manning.com / catalog / Data Science / Machine Learning
(2)
Ekaterina Kochmar , 2022
(1)
Ajay Thampi , 2022
Qingquan Song, Haifeng Jin, and Xia Hu , 2022
(7)
Ben Wilson , 2022
(13)
Luis G. Serrano
Foreword by Sebastian Thrun
, 2021
(2)
Masato Hagiwara , 2021
(11)
Alexey Grigorev , 2021
(2)
Andrew R. Freed , 2021
(4)
Alessandro Negro , 2021
(8)
Robert (Munro) Monarch , 2021
(3)
Paul Azunre , 2021
(5)
Chris A. Mattmann , 2020
(4)
Mohamed Elgendy , 2020
(5)
Hefin I. Rhys , 2020
Doug Hudgeon, Richard Nichol , 2019
(5)
Nicholas Chase , 2019
George-Bogdan Ivanov , 2019
(5)
Hobson Lane, Cole Howard, Hannes Hapke
Foreword by Dr. Arwen Griffioen
, 2019
Jeff Smith
Foreword by Sean Owen
, 2018
Nishant Shukla
with Kenneth Fricklas
, 2018
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
Avi Pfeffer
Foreword by Stuart Russell
, 2016
Peter Harrington , 2012
Sean Owen, Robin Anil, Ted Dunning, and Ellen Friedman , 2011
Haralambos Marmanis and Dmitry Babenko , 2009
Satnam Alag , 2008
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Dive into the transformative world of Machine Learning, where cutting-edge algorithms meet practical applications. From fundamental neural networks to advanced deep learning techniques, explore comprehensive resources that cover supervised, unsupervised, and reinforcement learning approaches. Master essential tools like TensorFlow, learn to build and deploy intelligent systems, and discover specialized applications in drug discovery, fraud detection, and anomaly identification. Delve into emerging technologies including Large Language Models (LLMs), transformers, and knowledge graphs, while gaining hands-on experience with computer vision, natural language processing, and automated decision-making systems. Whether you're interested in building chatbots, implementing computer vision solutions, or developing scalable machine learning platforms, find the expertise to turn data into actionable intelligence. For a more detailed breakdown, take a look at the following categories: Computer Vision Distributed Machine Learning Interpretable Machine Learning Knowledge Graphs Machine Learning Algorithms Natural Language Processing Natural Language Processing (NLP) Quantum Computing/Programming