Neural Networks for Time Series Forecasting with R: An Intuitive Step by Step Blueprint for Beginners

by N.D. Lewis

Finally, A Blueprint for Neural Network Time Series Forecasting with R! Neural Networks for Time Series Forecasting 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 neural network models for time series forecasting 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 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 neural networks for time series forecasting for yourself. YOUR PERSONAL BLUE Through a simple to follow step by step process, you will learn how to build neural network 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 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 This guide was written for people just like you. Individuals who want to get up to speed as quickly as possible. In this book you will learn how YOU'LL LEARN HOW Unleash the power of Long Short-Term Memory Neural Networks. Develop hands on skills using the Gated Recurrent Unit Neural Network. Design successful applications with Recurrent Neural Networks. Deploy Jordan and Elman Partially Recurrent Neural Networks. Adapt Deep Neural Networks for Time Series Forecasting. Master the General Method of Data Handling Type Neural Networks. For each neural network 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. Everything you need to get started is contained within this book. Neural Networks for Time Series Forecasting with R is your very own hands on practical, tactical, easy to follow guide to mastery. Buy this book today and accelerate your progress!

Kindle Edition

Published April 9, 2017

Reviews

[Shubhang Goswami · Rating 5 out of 5]

Exactly what I expected it to be. It is a recipe book for using deep learning techniques in R for time series. It won't go in depth at all, will give you the names and a brief overview of the different neural net structures used today. This book has ready to use examples that you can lift from the book straight away. Great for first timers!

A good resource if you work with R and time series data.

Note: Nowadays there is keras that is intuitive for R. The packages in the book are old, and keras would be a better toolkit to use. But nonetheless, you will still find this book useful!