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Time Series Forecasting in Python you own this product

Marco Peixeiro
  • MEAP began October 2021
  • Publication in Spring 2022 (estimated)
  • ISBN 9781617299889
  • 400 pages (estimated)
  • printed in black & white
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Does a great job at teaching time series analysis. The code is succint and clean, with a great use of figures and equations.

Gustavo Patino
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Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting.

In Time Series Forecasting in Python you will learn how to:

  • Recognize a time series forecasting problem and build a performant predictive model
  • Create univariate forecasting models that account for seasonal effects and external variables
  • Build multivariate forecasting models to predict many time series at once
  • Leverage large datasets by using deep learning for forecasting time series
  • Automate the forecasting process

Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You’ll explore interesting real-world datasets like Google’s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.

about the technology

Time series forecasting reveals hidden trends and makes predictions about the future from your data. This powerful technique has proven incredibly valuable across multiple fields—from tracking business metrics, to healthcare and the sciences. Modern Python libraries and powerful deep learning tools have opened up new methods and utilities for making practical time series forecasts.

about the book

Time Series Forecasting in Python teaches you to apply time series forecasting and get immediate, meaningful predictions. You’ll learn both traditional statistical and new deep learning models for time series forecasting, all fully illustrated with Python source code. Test your skills with hands-on projects for forecasting air travel, volume of drug prescriptions, and the earnings of Johnson & Johnson. By the time you’re done, you’ll be ready to build accurate and insightful forecasting models with tools from the Python ecosystem.

about the reader

For data scientists familiar with the basics of Python and TensorFlow.

about the author

Marco Peixeiro is a seasoned data science instructor who has worked as a data scientist for one of Canada’s largest banks. He is an active contributor to Towards Data Science, an instructor on Udemy, and on YouTube in collaboration with freeCodeCamp.

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Great book for developing a strong and practical understanding of time series analysis using modern techniques and tools.

Dan Sheikh

If you know little bit of Python and want to learn how to apply time series to your problem, then read this book!

Lokesh Kumar

A great introduction to time series modelling techniques.

Shreesha Jagadeesh
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