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


Congratulations on finishing yet another chapter. What you learned in this chapter is crucial for several complex machine learning activities. All the algorithms discussed in this chapter give a view of the underlying principals from several given examples (also called training sets). These types of algorithms are broadly classified under supervised learning.

You learnt how to use K-NN, a logistic regression model, and a J48 decision tree to predict the class/tag of an unknown entry.

In the next chapter, you will learn how to find similar products or items using several information retrieval metrics.