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

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 Features:

• 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

Book 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.

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

Who 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.

使用Python建立和使用當今最受歡迎的時間序列索引，以便在子序列級別上搜索和連接時間序列。

購買印刷版或Kindle書籍將包含免費的PDF電子書。

主要特點：
- 學習如何實現研究論文中的算法和技術
- 掌握使用iSAX建立時間序列索引
- 利用iSAX解決現實世界的時間序列問題

書籍描述：
時間序列無處不在，從金融數據和系統指標到氣象站和醫療記錄。能夠快速訪問、搜索和比較時間序列數據至關重要，這本全面的指南將幫助您通過探索SAX表示和最有效的時間序列索引iSAX實現這一目標。

本書首先教您如何在Python中實現SAX表示以及iSAX索引，並提供了來自學術研究論文的必要理論。章節中充滿了圖表和圖形，以幫助您理解所介紹的主題和關鍵概念。但這本書真正出色之處在於它包含了關於時間序列索引的適量理論和實踐知識，讓您能夠成功地使用時間序列並開發時間序列索引。此外，所提供的代碼可以輕鬆移植到任何其他現代編程語言，如Swift、Java、C、C++、Ruby、Kotlin、Go、Rust和JavaScript。

通過閱讀本書，您將學習如何利用iSAX和SAX表示高效地索引和分析時間序列數據，並具備開發自己的時間序列索引並有效處理時間序列數據的能力。

您將學到：
- 瞭解如何開發自己的Python套件並編寫簡單的Python測試
- 理解時間序列索引的定義及其用途
- 理論和實踐上理解操作和創建時間序列索引
- 使用SAX表示和iSAX索引
- 搜索和比較時間序列
- 利用iSAX可視化工具來解釋複雜或大型時間序列

本書適合對時間序列感興趣的從業人員、大學生、研究人員以及任何想要深入了解時間序列的人。需要具備UNIX、Linux和Python的基本知識，以及對基本編程概念的理解，才能理解本書中的主題。本書還對於想要學習如何閱讀研究論文、從中學習並實現其算法的人來說也很有用。