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


Anomaly detection is a very active field of research because what's anomalous now may not remain anomalous forever. This poses a significant challenge to designing a good anomaly detection algorithm. Although the algorithms discussed in this chapter mostly deal with point anomalies, they can be also used to detect sequential anomalies with a little bit of feature extraction.

Sometimes, anomaly detection is treated as a classification problem, and several classification algorithms such as k-NN, SVM, and Neural Networks are deployed to identify anomalous entries. The challenge, however, is to get well-labeled data. However, some heuristics are used to assign a score called the anomaly score to each data element, and then the top few with the highest anomaly scores (sometimes above a given threshold) are determined to be anomalous.

Anomaly detection has several applications, such as finding imposters using anomaly detection on keyboard dynamics, pedestrians, and landmine detection from...