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 time series forecasting models with R. Whether you are new to data science 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: This book uses plain language rather than a ton of equations; I’m assuming you never did like linear algebra, don’t want to see things derived, dislike complicated computer code, and you’re here because you want to try time series forecasting for yourself.
YOUR PERSONAL BLUE PRINT: Through a simple to follow step by step process you will learn how to build modern 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.
THIS BOOK IS FOR YOU IF YOU WANT:
• Explanations rather than mathematical derivation.
• Practical illustrations that use real data.
• Worked examples in R you can easily follow and immediately implement.
• Ideas you can actually use and try out with your own data.
TAKE THE SHORTCUT: Automated Time Series Forecasting Made Easy with R was written for people who want to get up to speed as quickly as possible.
In this book you will learn how to:
• Unleash the power of Facebook's Prophet forecasting algorithm.
• Master the 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.
QUICK AND EASY: For each time series model, 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.
Overview of Book
Chapter 1: Introduction to Time Series Analysis with R
Chapter 2: Maximizing Use of Simple Moving Averages
Chapter 3: Exploring Simple Exponential Smoothing
Chapter 4: Using Component Form Exponential Smoothing
Chapter 5: Working with the Theta Method
Chapter 6: A Practical Introduction to ARIMA Modeling
Chapter 7: Mastering BATS and TBATS Forecasting Techniques
Chapter 8: The Multiple Aggregation Prediction Algorithm
Chapter 9: Effective Forecasting Using the Prophet Algorithm
Chapter 10: Final Thoughts
Hands on Projects Include:
• Predicting Medical Product Use.
• Forecasting Milk Production.
• Modeling Carbon Monoxide Concentrations
• Forecasting Gun Sales.
• Prediction of Cardiovascular Mortality.
• Modeling Electricity Consumption.
• Forecasting Wikipedia Page Views.
GET STARTED TODAY! 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!