Machine Learning Projects for .NET Developers 1st edition

Publisher Marketing: Software that learns from experience can improve far beyond what a single developer, or even a large team, can write into its code. This is machine learning and it's already influencing a huge range of industries, from advertising to finance, medicine and the most cutting edge scientific research. Machine Learning Projects for . NET Developers is your practical and accessible introduction to this exciting area of software development. The book emphasizes a functional style of coding that promotes bug-free, reusable code that can be easily parallelized for scalable performance. You ll code each project in the familiar setting of a C# application, while the machine learning logic uses F#, a language ideally suited to machine learning applications and the logical choice for machine learning in . NET. If you re new to F#, this book will give you everything you need to get started. If you re already familiar with F#, this is your chance to put the language into action in an exciting new context, discover new techniques, and find out how seamlessly it can integrate with your C# applications. In a series of fascinating projects, you ll learn how to: Build an optical character recognition (OCR) system from scratchCode a spam filter that learns by exampleUse F# s powerful type providers to interface seamlessly with external resources (in this case, useful data analysis tools from the R programming language) Clean up incomplete data and use it to make accurate predictionsBuild a smart recommendation engine Find patterns in data when you don t know what you re looking forPredict numerical values using regression modelsAccurately spot trends and anomalies Along the way, you ll have fun hacking at data, learn fundamental ideas that can be applied in a broad range of real-world contexts, and discover new ways to simplify and approach real-world coding challenges. With Machine Learning Projects for . NET Developers, you'll expand your skill set as a . NET developer, gain a new understanding of data, and have fun working on challenging, mind-expanding problems! What you'll learn Learn vocabulary and landscape of machine learningRecognize patterns in problems and how to solve themLearn simple prediction algorithms and how to apply themDevelop, diagnose and tune your modelsWrite elegant, efficient and bug-free functional code with F# Who this book is for Machine Learning Projects for . NET Developers is for intermediate to advanced . NET developers who are comfortable with C#. No prior experience of machine learning techniques is required. If you re new to F#, you ll find everything you need to get started. If you re already familiar with F#, you ll find a wealth of new techniques here to interest and inspire you. While some machine learning algorithms use fairly advanced mathematics, this book focuses on simple but effective approaches and how they can be used in actual code. If you enjoy hacking code and data, this book is for you. "

Contributor Bio:  Brandewinder, Mathias Mathias Brandewinder is a Microsoft MVP for F# based in San Francisco, California. An unashamed math geek, he became interested early on in building models to help others make better decisions using data. He collected graduate degrees in Business, Economics and Operations Research, and fell in love with programming shortly after arriving in the Silicon Valley. He has been developing software professionally since the early days of . NET, developing business applications for a variety of industries, with a focus on predictive models and risk analysis.