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Hands-On Time Series Analysis with R. Build accurate forecasting models using ARIMA, Prophet, TBATS, Bayesian methods, and deep learning - Second Edition Diogo Alves de Resende, Shuen Mei

Książka w języku angielskim angielski
Hands-On Time Series Analysis with R. Build accurate forecasting models using ARIMA, Prophet, TBATS, Bayesian methods, and deep learning - Second Edition Diogo Alves de Resende, Shuen Mei - okladka książki

Hands-On Time Series Analysis with R. Build accurate forecasting models using ARIMA, Prophet, TBATS, Bayesian methods, and deep learning - Second Edition Diogo Alves de Resende, Shuen Mei - okladka książki

Hands-On Time Series Analysis with R. Build accurate forecasting models using ARIMA, Prophet, TBATS, Bayesian methods, and deep learning - Second Edition Diogo Alves de Resende, Shuen Mei - audiobook MP3

Hands-On Time Series Analysis with R. Build accurate forecasting models using ARIMA, Prophet, TBATS, Bayesian methods, and deep learning - Second Edition Diogo Alves de Resende, Shuen Mei - audiobook CD

Autorzy:
Diogo Alves de Resende, Shuen Mei
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
402
Dostępne formaty:
     PDF
     ePub

Ebook
116,10 zł 129,00 zł (-10%)
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Do przechowalni

Hands-on Time Series Analysis with R, Second Edition, is a comprehensive, practical guide to understanding and applying time series analysis using R. Designed for professionals and students alike, the book will help you dissect time-ordered data, uncover trends, detect anomalies, and forecast future events.

You’ll start with R fundamentals and data structures, progressing through time series visualization and decomposition,before covering classical forecasting methods like exponential smoothing and ARIMA. You’ll also familiarize yourself with cutting-edge forecasting techniques such as Bayesian modeling, TBATS, and multivariate forecasting.

Building upon the extraordinary success of the first edition, this new edition explores the powerful Prophet library, neural networks, and LSTM models to handle complex forecasting challenges. Unlike other similar books, it uses real-world case studies from domains like e-commerce and supply chain make the content highly applicable, while self-assessment questions and step-by-step tutorials reinforce key concepts.

By the end of this book, you’ll be able to confidently apply a wide array of forecasting methods to solve real-world business and research problems.

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O autorach książki

Diogo Alves de Resende is the founder of The Data Hero and Bitte, with deep expertise in time series and commercial analytics. Formerly a senior commercial analyst at Zalando, he has implemented forecasting models for demand planning and return rates. As a popular Udemy instructor with over 20,000 students, Diogo brings his educational background and entrepreneurial experience into accessible, real-world teaching. He holds an MSc in Management and continues to blend technical insight with applied business strategy.
Shuen Mei is a big data analytic platforms expert with 15+ years of experience in designing, building, and executing large-scale, enterprise-distributed financial systems with mission-critical low-latency requirements. He is certified in the Apache Spark, Cloudera Big Data platform, including Developer, Admin, and HBase. He is also a certified AWS solutions architect with emphasis on peta-byte range real-time data platform systems.

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