Hands-On Machine Learning with C#: Building smarter, speedy and reliable data-intensive applications using machine learning

Hands-On Machine Learning with C#: Building smarter, speedy and reliable data-intensive applications using machine learning

Explore Supervised, Unsupervised Learning Techniques and Bring Smart Features to your ApplicationsKey FeaturesLeverage Machine Learning techniques to build smart, predictive and real-world applicationsAccord.Net machine learning framework for reinforcement learningMachine learning techniques using various libraries-Accord, Numl, EncogBook DescriptionIn our daily work which is predominantly Information Technology, the necessity of machine learning is everywhere and demanded by all developers, programmers, and analysts. But why C# for machine learning? The answer is most of the Microsoft enterprise applications are written in C# such as Visual Studio, SQL Server, Photoshop and various mobile applications, Unity platform, Microsoft Azure, StackOverflow and so on.This book develops the intuitive understanding of various concepts, techniques of machine learning and various available machine learning tools through which they can add intelligent features such as sentiment detection, speech recognition, language understanding, smart search and so on to C# and .NET applications.Using this book, you will implement supervised and unsupervised learning algorithms and will be getting well equipped to create better predictive models. You will learn numerous techniques and algorithms right from a simple linear regression, decision trees, SVM to advanced concepts such as artificial neural networks, autoencoders, and reinforcement learning.By the end of this book, the readers will develop a machine learning mindset and can leverage the tools, techniques, and packages of C# in building smart, predictive and real-world business applicationsWhat you will learnLearn how to parameterize a probabilistic problemUse Naïve Bayes to visually plot and analyze dataPlot a text-based representation of a decision tree using numlUse the Accord.Net machine learning framework for associative rule-based learningDevelop machine learning algorithms utilizing fuzzy logicExplore Support Vector Machines for image recognitionUnderstand Dynamic Time Warping for sequence recognitionWho This Book Is ForThis book is meant for all developers and programmers working on a range of platforms from .NET and Windows to mobile devices. Basic knowledge of statistics is required.About the AuthorMatt R. Cole is a seasoned developer with 30 years’ experience in Microsoft Windows, C, C++, C# and .Net. He is the owner of Evolved AI Solutions, a premier provider of advanced Machine Learning/Bio-AI technologies. He is also the first enterprise-grade MicroService framework written completely in C# and .Net, which is used in production by a major hedge fund in NYC. Matt also developed the first Bio Artificial Intelligence framework which completely integrates mirror and canonical neurons.

Author: Matt R. Cole

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