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Key benefits

Learn how to implement algorithms and techniques from research papers

Get to grips with building time series indexes using iSAX

Leverage iSAX to solve real-world time series problems

Description

Time series are everywhere, ranging from financial data and system metrics to weather stations and medical records. Being able to access, search, and compare time series data quickly is essential, and this comprehensive guide enables you to do just that by helping you explore SAX representation and the most effective time series index, iSAX. The book begins by teaching you about the implementation of SAX representation in Python as well as the iSAX index, along with the required theory sourced from academic research papers. The chapters are filled with figures and plots to help you follow the presented topics and understand key concepts easily. But what makes this book really great is that it contains the right amount of knowledge about time series indexing using the right amount of theory and practice so that you can work with time series and develop time series indexes successfully. Additionally, the presented code can be easily ported to any other modern programming language, such as Swift, Java, C, C++, Ruby, Kotlin, Go, Rust, and JavaScript. By the end of this book, you'll have learned how to harness the power of iSAX and SAX representation to efficiently index and analyze time series data and will be equipped to develop your own time series indexes and effectively work with time series data.

Who is this book for?

This book is for practitioners, university students working with time series, researchers, and anyone looking to learn more about time series. Basic knowledge of UNIX, Linux, and Python and an understanding of basic programming concepts are needed to grasp the topics in this book. This book will also be handy for people who want to learn how to read research papers, learn from them, and implement their algorithms.

What you will learn

Find out how to develop your own Python packages and write simple Python tests

Understand what a time series index is and why it is useful

Gain a theoretical and practical understanding of operating and creating time series indexes

Discover how to use SAX representation and the iSAX index

Find out how to search and compare time series

Utilize iSAX visualizations to aid in the interpretation of complex or large time series

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Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

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AI Assistant (beta) to help accelerate your learning

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No name Jul 14, 2023

iSAX is a advanced time series index that is difficult to understand. This book is going to teach you how to create an iSAX index, how to compute the SAX representation and how to work with time series at the subsequence level. Highly recommended!

Amazon Verified review

Om S Jul 05, 2023

Time Series Indexing: Implement iSAX in Python to Index Time Series with Confidence" is a comprehensive guide that equips practitioners, researchers, and students with the knowledge and skills to effectively access, search, and analyze time series data. The book introduces SAX representation in Python and explores the powerful iSAX index, supported by academic research papers. With a perfect balance of theory and practice, readers learn to create and operate time series indexes, search and compare time series, and utilize iSAX visualizations. The provided code samples are easily adaptable to other programming languages. This indispensable resource empowers readers to develop their own indexes and confidently work with time series data.

MT Nov 18, 2023

Time series is a huge subject. This book is going to help you understand time series basics and help you create iSAX indexes for fast subsequence searching.

Time Series Indexing: Implement iSAX in Python to index time series with confidence

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