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

Free Download Time Series Indexing: Implement iSAX in Python to index time series with confidence by Mihalis Tsoukalos
English | June 30, 2023 | ISBN: 1838821953 | 248 pages | PDF | 14 Mb
Build and use the most popular time series index available today with Python to search and join time series at the subsequence level

Purchase of the print or Kindle book includes a free PDF eBook
Key FeaturesLearn how to implement algorithms and techniques from research papersGet to grips with building time series indexes using iSAXLeverage iSAX to solve real-world time series problemsBook 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 Descriptions 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.
What you will learnFind out how to develop your own Python packages and write simple Python testsUnderstand what a time series index is and why it is usefulGain a theoretical and practical understanding of operating and creating time series indexesDiscover how to use SAX representation and the iSAX indexFind out how to search and compare time seriesUtilize iSAX visualizations to aid in the interpretation of complex or large time seriesWho this book is 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.
Table of ContentsAn Introduction to Time Series and the Required Python KnowledgeImplementing SAXiSAX – The Required TheoryiSAX – The implementationJoining and Comparing iSAX IndexesVisualizing iSAX IndexesUsing iSAX to Approximate MPdistConclusions and Next Steps

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