Neural Networks Books



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Hands-On Machine Learning with C++

Hands-On Machine Learning with C++

by Kirill Kolodiazhnyi

C++ can make your machine learning models run faster and more efficiently. This handy guide will help you learn the fundamentals of machine learning (ML), showing you how to use C++ libraries to get the most out of your data. This book makes machine learning with C++ for beginners easy with its example-based approach, demonstrating how to implement supervised and unsupervised ML algorithms through real-worl...

Price:  $31.19  |  Publisher:  Packt Publishing  |  Release:  2020

Python Machine Learning By Example, 3rd Edition

Python Machine Learning By Example, 3rd Edition

by Yuxi (Hayden) Liu

Python Machine Learning By Example, 3rd Edition serves as a comprehensive gateway into the world of machine learning (ML).With six new chapters, on topics including movie recommendation engine development with Naïve Bayes, recognizing faces with support vector machine, predicting stock prices with artificial neural networks, categorizing images of clothing with convolutional neural networks, predicting wit...

Price:  $34.99  |  Publisher:  Packt Publishing  |  Release:  2020

Mastering Machine Learning Algorithms, 2nd Edition

Mastering Machine Learning Algorithms, 2nd Edition

by Giuseppe Bonaccorso

Mastering Machine Learning Algorithms, 2nd Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and unsupervised learning domains.You will use all the m...

Price:  $40.49  |  Publisher:  Packt Publishing  |  Release:  2020

Advanced Deep Learning with TensorFlow 2 and Keras, 2nd Edition

Advanced Deep Learning with TensorFlow 2 and Keras, 2nd Edition

by Rowel Atienza

Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised for TensorFlow 2.x, this edition introduces you to the practical side of deep learning with new chapters on unsupervised learning using mutual information, object detection (SSD), and semantic segmentation (FCN and PSPNe...

Price:  $39.99  |  Publisher:  Packt Publishing  |  Release:  2020

Artificial Intelligence By Example, 2nd Edition

Artificial Intelligence By Example, 2nd Edition

by Denis Rothman

Artificial intelligence (AI) has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples.This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from comp...

Price:  $39.99  |  Publisher:  Packt Publishing  |  Release:  2020

Artificial Neural Networks with Java

Artificial Neural Networks with Java

by Igor Livshin

Use Java to develop neural network applications in this practical book. After learning the rules involved in neural network processing, you will manually process the first neural network example. This covers the internals of front and back propagation, and facilitates the understanding of the main principles of neural network processing. Artificial Neural Networks with Java also teaches you how to prepare t...

Price:  $13.62  |  Publisher:  Apress  |  Release:  2019

Neural Networks with JavaScript Succinctly

FREE EBOOK - Neural Networks with JavaScript Succinctly

by James McCaffrey

James McCaffrey leads you through the fundamental concepts of neural networks, including their architecture, input-output, tanh and softmax activation, back-propagation, error and accuracy, normalization and encoding, and model interpretation. Although most concepts are relatively simple, there are many of them, and they interact with each other in unobvious ways, which is a major challenge of neural networ...

Publisher:  Syncfusion  |  Release:  2019

Learn Keras for Deep Neural Networks

Learn Keras for Deep Neural Networks

by Jojo John Moolayil

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.The overall book comprises three sections with two chapters in each section. The first section prepares...

Price:  $9.99  |  Publisher:  Apress  |  Release:  2019

The Big Book of Machine Learning Use Cases

FREE EBOOK - The Big Book of Machine Learning Use Cases

by Ricardo Portilla, Brenner Heintz, Denny Lee

The world of machine learning is evolving so quickly that it's challenging to find real-life use cases that are relevant to your day-to-day work.That's why we've created this comprehensive guide you can start using right away. Get everything you need - use cases, code samples and notebooks - so you can start putting the Databricks Lakehouse Platform to work today.Plus, you'll get case st...

Publisher:  Self-publishing  |  Release:  2019

Python Machine Learning Projects

FREE EBOOK - Python Machine Learning Projects

by Lisa Tagliaferri, Michelle Morales, Ellie Birkbeck, Alvin Wan

As machine learning is increasingly leveraged to find patterns, conduct analysis, and make decisions - sometimes without final input from humans who may be impacted by these findings - it is crucial to invest in bringing more stakeholders into the fold. This book of Python projects in machine learning tries to do just that: to equip the developers of today and tomorrow with tools they can use to better unde...

Publisher:  DigitalOcean  |  Release:  2019

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