Mastering Machine Learning with Python in Six Steps 
by Manohar Swamynathan
Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book's approach is based on the "Six degrees of separation" theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning with Python in Six Steps presents each topic in two parts: theoretical c...
Price: $37.64 | Publisher: Apress | Release: 2017
by Adam Gibson, Josh Patterson
Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning - especially deep neural networks - make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks.Auth...
Price: $15.99 | Publisher: O'Reilly Media | Release: 2017
by Nikhil Buduma
With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that's paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field.Companies such as Google, Microsoft, and Facebook are actively growing in-house de...
Price: $30.45 | Publisher: O'Reilly Media | Release: 2017
Hands-On Machine Learning with Scikit-Learn and TensorFlow
by Aurelien Geron
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. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks - scikit-learn and TensorFlo...
Price: $19.50 | Publisher: O'Reilly Media | Release: 2017
by Itay Lieder, Yehezkel Resheff, Tom Hope
Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. 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.Aut...
Price: $12.69 | Publisher: O'Reilly Media | Release: 2017
FREE EBOOK - An Introduction to Machine Learning, 2nd Edition
by Miroslav Kubat
This book 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. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how t...
Price: $65.87 | Publisher: Springer | Release: 2017
FREE EBOOK - Neural Network Programming with Java
by Alan M.F. Souza, Fabio M. Soares
Vast quantities of data are produced every second. In this context, neural networks become a powerful technique to extract useful knowledge from large amounts of raw, seemingly unrelated data. One of the most preferred languages for neural network programming is Java as it is easier to write code using it, and most of the most popular neural network packages around already exist for Java. This makes it a ve...
Price: $44.99 | Publisher: Packt Publishing | Release: 2016
FREE EBOOK - Exploring Data Science
by John Mount, Nina Zumel
There's never been a better time to get into data science. But where do you start? Data Science is a broad field, incorporating aspects of statistics, machine learning, and data engineering. It's easy to become overwhelmed, or end up learning about a small section of data science or a single methodology.Exploring Data Science is a collection of five hand-picked chapters introducing you to various ...
Publisher: Manning | Release: 2016
F# for Machine Learning Essentials
by Sudipta Mukherjee
The F# functional programming language enables developers to write simple code to solve complex problems. With F#, developers create consistent and predictable programs that are easier to test and reuse, simpler to parallelize, and are less prone to bugs.If you want to learn how to use F# to build machine learning systems, then this is the book you want.Starting with an introduction to the several categorie...
Price: $39.99 | Publisher: Packt Publishing | Release: 2016
FREE EBOOK - Efficient Learning Machines
by Mariette Awad, Rahul Khanna
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel ...
Price: $39.99 | Publisher: Apress | Release: 2015