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

Introduction to time series analysis


There are several occasions when we might try to observe and capture an event at different points in time. Often, we would end up drawing a correlation or association between adjacent observations that cannot be handled by an approach that deals with data that is independent and identically distributed. The approach that takes all of this into consideration in a mathematical and statistical manner is called time series analysis.

Time series analysis has been used in a number of fields, such as the automotive, banking, and retail industries, product development, and so on. There is no boundary for its use, and so analysts and data scientists are exploring this area to the hilt in order to derive the maximum benefit for organizations.

In this section, we will go through a few of the concepts around time series analysis that will lay the foundation for a deeper understanding in the future. Once we have established this foundation, we will jump into modeling...