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

Chapter 1. Introduction to Machine Learning

"To learn is to discover patterns."

You have been using products that employ machine learning, but maybe you've never realized that the systems or programs that you have been using, use machine learning under the hood. Most of what machine learning does today is inspired by sci-fi movies. Machine learning scientists and researchers are on a perpetual quest to make the gap between the sci-fi movies and the reality disappear. Learning about machine learning algorithms can be fun.

This is going to be a very practical book about machine learning. Throughout the book I will be using several machine learning frameworks adopted by the industry. So I will cut the theory of machine learning short and will get away with just enough to implement it. My objective in this chapter is to get you excited about machine learning by showing how you can use these techniques to solve real world problems.