Matt R. Cole - Hands-On Machine Learning with C#

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First published: May 2018

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ISBN 978-1-78899-494-1

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Matt R. Cole is a seasoned developer with 30 years' experience in Microsoft Windows, C, C++, C#, and .NET. He previously wrote a speech and audio VOIP system for NASA for use with the Space Shuttle and a space station. He is the owner of Evolved AI Solutions, a premier provider of advanced ML/Bio-AI technologies. He developed the first enterprise-grade microservice framework (written fully in C# and .NET) used by a major hedge fund in NYC and he also developed the first Bio-AI Swarm framework, which fully integrates mirror and canonical neurons.

Giuseppe Ciaburro holds a PhD in environmental technical physics and two master's degrees. His research is on machine learning applications in the study of urban sound environments. He works at the Built Environment Control Laboratory, Universit degli Studi della Campania Luigi Vanvitelli (Italy). He has over 15 years' experience in programming Python, R, and MATLAB, first in the field of combustion, and then in acoustics and noise control. He has several publications to his credit.

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In our daily work, which is predominantly information technology, the necessity of machine learning is everywhere and is demanded by all developers, programmers, and analysts. But why use C# for machine learning? The answer is, most production enterprise applications are written in C# using tools such as Visual Studio, SQL Server, Unity, and Microsoft Azure.

This book provides an intuitive understanding of various concepts, the techniques of machine learning, and various machine learning tools through which users can add intelligent features such as image and motion detection, Bayes intuition, deep learning and belief, and more to C# .NET applications.

Using this book, you will implement supervised and unsupervised learning algorithms and will be well equipped to create good predictive models. You will learn numerous techniques and algorithms, right from simple linear regression, decision trees, and SVM to advanced concepts such as artificial neural networks, autoencoders, and reinforcement learning.

By the end of this book, you will have developed a machine learning mindset and will be able to leverage C# tools, techniques, and packages to build smart, predictive, and real-world business applications.

This book is for developers with experience of C# and .NET. No other experience is require or assumedjust a passion for machine learning, artificial intelligence, and deep learning.

, Machine Learning Basics, provides an introduction to machine learning as well as what we hope to accomplish in this book.

, ReflectInsight Real-Time Monitoring , introduces ReflectInsight, a powerful, flexible, and rich framework that we will use throughout the book for logging and insight into our algorithms.

, Bayes Intuition Solving the Hit and Run Mystery and Performing Data Analysis , exposes the reader to Bayes intuition. We will also examine and solve the famous "hit and run" problem, where we try to determine who fled the scene of an accident.

, Risk versus Reward Reinforcement Learning , shows how reinforcement learning works.

, Fuzzy Logic Navigating the Obstacle Course , implements fuzzy logic to guide our autonomous guided vehicle around an obstacle course. We'll show how to load various maps, and how our autonomous vehicle receives rewards and penalties for making correct and incorrect decisions.