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
About the Author
About the Reviewers


In this chapter, you learned about several linear regression models. I hope you will find this information useful to solve some of your own practical problems. For example, you can predict your next electrical bill by doing a historical survey of your old bills. When not sure, start with a single predictor and gradually add more predictors to find a suitable model. Also, you can ask domain experts to locate predictor variables. Although there can be a temptation to use linear regression for prediction, don't give in. Linear regression can't work that way.

In the next chapter, you will learn about several supervised learning algorithms for classification. I hope you have enjoyed reading this chapter.