Book description
Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-world problems. You’ll code each project in the familiar setting of Visual Studio, while the machine learning logic uses F#, a language ideally suited to machine learning applications 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.
In a series of fascinating projects, you’ll learn how to:
Along the way, you’ll learn fundamental ideas that can be applied in all kinds of real-world contexts and industries, from advertising to finance, medicine, and scientific research. While some machine learning algorithms use fairly advanced mathematics, this book focuses on simple but effective approaches. If you enjoy hacking code and data, this book is for you.
Table of contents
- Cover
- Title
- Copyright
- Contents at a Glance
- Contents
- About the Author
- About the Technical Reviewer
- Acknowledgments
- Introduction
- Chapter 1: 256 Shades of Gray
- Chapter 2: Spam or Ham?
- Chapter 3: The Joy of Type Providers
- Chapter 4: Of Bikes and Men
-
Chapter 5: You Are Not a Unique Snowflake
- Detecting Patterns in Data
- Our Challenge: Understanding Topics on StackOverflow
- Finding Clusters with K-Means Clustering
- Clustering StackOverflow Tags
- Good Clusters, Bad Clusters
- Rescaling Our Dataset to Improve Clusters
- Identifying How Many Clusters to Search For
- Detecting How Features Are Related
- Identifying Better Features with Principal Component Analysis
- Making Recommendations
- So What Have We Learned?
- Chapter 6: Trees and Forests
- Chapter 7: A Strange Game
- Chapter 8: Digits, Revisited
- Chapter 9: Conclusion
- Index
Product information
- Title: Machine Learning Projects for .NET Developers
- Author(s):
- Release date: July 2015
- Publisher(s): Apress
- ISBN: 9781430267669
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