Automated Time Series Forecasting Made Easy with R: An intuitive Step by Step Introduction for Data Science

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Description

Finally, A Blueprint for Automated Time Series Forecasting with R!

Automated Time Series Forecasting Made Easy with R offers a practical tutorial that uses hands-on examples to step through real-world applications using clear and practical case studies. Through this process it takes you on a gentle, fun and unhurried journey to creating your own models to forecast time series data. Whether you are new to time series forecasting or a veteran, this book offers a powerful set of tools for quickly and easily gaining insight from your data using R.

NO EXPERIENCE REQUIRED: Through a simple to follow step by step process you will learn how to build time series forecasting models using R. Once you have mastered the process, it will be easy for you to translate your knowledge into your own powerful applications.

YOUR PERSONAL BLUE PRINT: Through a simple to follow intuitive step by step process, you will learn how to use the most popular time series forecasting models using R. Once you have mastered the process, it will be easy for you to translate your knowledge to assess your own data.

THIS BOOK IS FOR YOU IF YOU WANT:
  • Focus on explanations rather than mathematical derivation
  • Practical illustrations that use real data.
  • Illustrations to deepen your understanding.
  • Worked examples in R you can easily follow and immediately implement.
  • Ideas you can actually use and try on your own data.


    • TAKE THE SHORTCUT: This guide was written for people who want to get up to speed as quickly as possible.

    YOU'LL LEARN HOW TO:
  • Unleash the power the Prophet forecasting algorithm.
  • Master the award winning Theta method.
  • Use the component form exponential smoothing framework.
  • Design successful applications using classical ARIMA modeling.
  • Adapt the flexible BATS and TBATS framework for optimum success.
  • Deploy the multiple aggregation prediction algorithm.
  • Explore the potential of simple moving averages.


    • For each time series forecasting technique, every step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks. Using plain language, this book offers a simple, intuitive, practical, non-mathematical, easy to follow guide to the most successful ideas, outstanding techniques and usable solutions available using R.

    Everything you need to get started is contained within this book. Automated Time Series Forecasting Made Easy with R is your very own hands on practical, tactical, easy to follow guide to mastery.

    Buy this book today and accelerate your progress!