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

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Time Series Indexing. Implement iSAX in Python to index time series with confidence Mihalis Tsoukalos - okladka książki

Time Series Indexing. Implement iSAX in Python to index time series with confidence Mihalis Tsoukalos - okladka książki

Autor:
Mihalis Tsoukalos
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
248
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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.

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O autorze książki

Mihalis Tsoukalos holds a BSc in Mathematics from the University of Patras and an MSc in IT from University College London, UK. His books, Go Systems Programming and Mastering Go, have become must-reads for Unix and Linux systems professionals. He enjoys writing technical articles and has written for Sys Admin, MacTech, C/C++ Users Journal, USENIX ;login:, Linux Journal, Linux User and Developer, Linux Format, and Linux Voice. His research interests include time series data mining, time series indexing, and databases.

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