Book Image

F# for Machine Learning Essentials

By : Sudipta Mukherjee
Book Image

F# for Machine Learning Essentials

By: Sudipta Mukherjee

Overview of this book

The F# functional programming language enables developers to write simple code to solve complex problems. With F#, developers create consistent and predictable programs that are easier to test and reuse, simpler to parallelize, and are less prone to bugs. If you want to learn how to use F# to build machine learning systems, then this is the book you want. Starting with an introduction to the several categories on machine learning, you will quickly learn to implement time-tested, supervised learning algorithms. You will gradually move on to solving problems on predicting housing pricing using Regression Analysis. You will then learn to use Accord.NET to implement SVM techniques and clustering. You will also learn to build a recommender system for your e-commerce site from scratch. Finally, you will dive into advanced topics such as implementing neural network algorithms while performing sentiment analysis on your data.
Table of Contents (16 chapters)
F# for Machine Learning Essentials
Credits
Foreword
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Index

Machine learning frameworks


I will be using the following machine learning frameworks to solve some of the real problems throughout the book:

  • Accord.NET (http://accord-framework.net/)

  • WekaSharp (http://accord-framework.net/)

You are much better off using these frameworks than creating your own because a lot of work has been done and they are used in the industry. So if you pick up using these frameworks along the way while learning about machine learning algorithms in general, that's a great thing. You will be in luck.