Book Image

Machine Learning Quick Reference

By : Rahul Kumar
Book Image

Machine Learning Quick Reference

By: Rahul Kumar

Overview of this book

Machine learning makes it possible to learn about the unknowns and gain hidden insights into your datasets by mastering many tools and techniques. This book guides you to do just that in a very compact manner. After giving a quick overview of what machine learning is all about, Machine Learning Quick Reference jumps right into its core algorithms and demonstrates how they can be applied to real-world scenarios. From model evaluation to optimizing their performance, this book will introduce you to the best practices in machine learning. Furthermore, you will also look at the more advanced aspects such as training neural networks and work with different kinds of data, such as text, time-series, and sequential data. Advanced methods and techniques such as causal inference, deep Gaussian processes, and more are also covered. By the end of this book, you will be able to train fast, accurate machine learning models at your fingertips, which you can easily use as a point of reference.
Table of Contents (18 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Chapter 6. Natural Language Processing

How fast has the world been changing? Well, technology and data have been changing just as quickly. With the advent of the internet and social media, our entire outlook on data has changed. Initially, the scope of most data analytics revolved around structured data. However, due to so much unstructured data being pumped in through the internet and social media, the spectrum of analytics has broadened. Large amounts of text data, images, sound, and video data are being generated every second. They contain lots of information that needs to be synthesized for business. Natural language processing is a technique through which we enable a machine to understand text or speech. Although unstructured data has a wide range, the scope of this chapter will be to expose you to text analytics.

Structured data is typically made up of fixed observations and fixed columns set up in relational databases or in a spreadsheet, whereas unstructured data doesn't have any...