Practical Time Series Forecasting with Python: A Hands-On Guide

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· Axelrod Schnall Publishers
Ebook
254
Pages
Eligible
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About this ebook

Practical Time Series Forecasting with Python: A Hands-On Guide provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. The book introduces popular forecasting methods and approaches used in a variety of business applications.

The book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods using the free open-source Python software to develop effective forecasting solutions that extract business value from time series data.

This edition includes:

- Popular forecasting methods including smoothing algorithms, regression models, ARIMA, neural networks, deep learning, and ensembles

- A practical approach to evaluating the performance of forecasting solutions

- A business-analytics exposition focused on linking time-series forecasting to business goals

- Guided cases for integrating the acquired knowledge using real data

- End-of-chapter problems to facilitate active learning

- Data, Python code, and instructor materials on companion website

- Affordable and globally-available textbook, available in hardcover, paperback, and ebook formats

Practical Time Series Forecasting with Python: A Hands-On Guide is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. The book is also designed for practitioners in the fields of operations research, supply chain management, marketing, economics, information systems, finance, and management.

About the author

Galit Shmueli is Chair Professor at the Institute of Service Science, College of Technology Management, National Tsing Hua University, Taiwan. She is co-author of the best-selling textbook Machine Learning for Business Analytics, among other books and numerous publications in top journals. She has designed and instructed courses on forecasting, machine learning, statistics and other data analytics topics at University of Maryland's Smith School of Business, the Indian School of Business, National Tsing Hua University, and online at statistics.com. 

Eric Berger was CEO and founder of Berger Financial Research Ltd. (BFR), which developed mathematical models of complex financial derivatives. After BFR was acquired by Bloomberg and became Bloomberg’s Israeli subsidiary, he was the CEO of Bloomberg/Israel. He subsequently was Chief Risk Officer (CRO) at Oasis Capital Management and is currently CRO at Eagle Labs Capital (Israel). Eric has a Ph.D. in Mathematics from Harvard University.

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