Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Practical Time Series Forecasting with Python: A Hands-On Guide

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

Berger, Eric
Shmueli, Galit

Paperback

Business General

ISBN10: 0997847964
ISBN13: 9780997847963
Publisher: Axelrod Schnall Publishers
Published: Jul 5 2025
Pages: 256
Weight: 0.99
Height: 0.54 Width: 7.00 Depth: 10.00
Language: English
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.

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