
Название: Machine Learning Mastery With Python: Understand Your Data, Create Accurate Models and Work Projects End-To-End
Автор: Jason Brownlee
Год: 2016
Страниц: 179
Формат: PDF
Размер: 10 Mb
Язык: English
The Python ecosystem with scikit-learn and pandas is required for operational machine learning.
Python is the rising platform for professional machine learning because you can use the same code to explore different models in R&D then deploy it directly to production.
In this mega Ebook written in the friendly Machine Learning Mastery style that you’re used to, learn exactly how to get started and apply machine learning using the Python ecosystem.

Автор: Celia Hodent
Название: The Gamer's Brain: How Neuroscience and UX Can Impact Video Game Design
Издательство: CRC Press
Год: 2017
ASIN: B074PTTKR7
Язык: English
Формат: azw3, pdf(conv)
Размер: 11,8 mb
Страниц: 272
This book is designed to equip readers of all levels, from student to professional, with neuroscience knowledge and user experience guidelines and methodologies.

Автор: Anne Boehm
Издательство: Mike Murach & Associates
Год: 2013
ISBN: 9781890774738
Формат: pdf
Страниц: 842
Размер: 142,4 mb
Язык: English
This 5th Edition is a self-paced, professional book that shows how to use Visual Studio 2012, VB 2012, and the .NET 4.5 classes to develop Windows Forms applications.

Автор: Lauren Darcey, Shane Conder
Издательство: Addison-Wesley Professional
Год: 2012
Формат: PDF, EPUB
Размер: 68 Мб
Язык: английский / English
Android Wireless Application Development has earned a reputation as the most useful real-world guide to building robust, commercial-grade Android apps. Now, authors Lauren Darcey and Shane Conder have systematically revised and updated this guide for the latest Android SDK 4.0. To accommodate their extensive new coverage, they’ve split the book into two volumes.

Название: C Primer Plus, 6th Edition
Автор: Stephen Prata
Издательство: Addison-Wesley Professional
Год: 2013
Страниц: 1080
Формат: True PDF, EPUB
Размер: 70 Mb
Язык: English
Primer Plus, 6th Edition is a carefully tested, well-crafted, and complete tutorial on a subject core to programmers and developers. This computer science classic teaches principles of programming, including structured code and top-down design.
Author and educator Stephen Prata has created an introduction to C that is instructive, clear, and insightful. Fundamental programming concepts are explained along with details of the C language. Many short, practical examples illustrate just one or two concepts at a time, encouraging readers to master new topics by immediately putting them to use.

Название: C Programming and Numerical Analysis: An Introduction
Автор: Seiichi Nomura
Издательство: Morgan & Claypool Publishers
Год: 2018
Страниц: 200
Формат: True PDF
Размер: 10 Mb
Язык: English
This book is aimed at those in engineering/scientific fields who have never learned programming before but are eager to master the C language quickly so as to immediately apply it to problem solving in numerical analysis. The book skips unnecessary formality but explains all the important aspects of C essential for numerical analysis. Topics covered in numerical analysis include single and simultaneous equations, differential equations, numerical integration, and simulations by random numbers. In the Appendices, quick tutorials for gnuplot, Octave/MATLAB, and FORTRAN for C users are provided.

Название: Neural Networks for Electronics Hobbyists: A Non-Technical Project-Based Introduction
Автор: Richard McKeon
Издательство: Apress
Год: 2018
Страниц: 139
Формат: PDF, EPUB
Размер: 10 Mb
Язык: English
Learn how to implement and build a neural network with this non-technical, project-based book as your guide. As you work through the chapters, you'll build an electronics project, providing a hands-on experience in training a network.
There are no prerequisites here and you won't see a single line of computer code in this book. Instead, it takes a hardware approach using very simple electronic components. You'll start off with an interesting non-technical introduction to neural networks, and then construct an electronics project. The project isn't complicated, but it illustrates how back propagation can be used to adjust connection strengths or "weights" and train a network.