Deep Time Series Forecasting with Python: An Intuitive Introduction to Deep Learning for Applied Time Series Modeling

Master Deep Time Series Forecasting with Python!

Deep Time Series Forecasting with Python takes you on a gentle, fun and unhurried practical journey to creating deep neural network models for time series forecasting with Python. It uses plain language rather than mathematics; And is designed for working professionals, office workers, economists, business analysts and computer users who want to try deep learning on their own time series data using Python.
QUICK AND EASY: 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 Python. Examples are clearly described and can be typed directly into Python as printed on the page.
NO EXPERIENCE? 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 see how to use deep learning for time series forecasting explained in plain language, and try it out for yourself.
THIS BOOK IS FOR YOU IF YOU WANT:

• Explanations rather than mathematical derivation
• Real world applications that make sense.
• Illustrations to deepen your understanding.
• Worked examples you can easily follow and immediately implement.
• Ideas you can actually use and try on your own data.

CUT LEARNING TIME IN HALF!: This guide was written for people who want to get up to speed as soon as possible. Through a simple to follow process you will learn how to build deep time series forecasting models in the minimum amount of time using Python. Once you have mastered the process, it will be easy for you to translate your knowledge into your own powerful business applications.
YOU’LL LEARN HOW TO:

• 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 Nonlinear Auto-regressive Network with Exogenous Inputs..
• Adapt Deep Neural Networks for Time Series Forecasting.
• Master strategies to build superior Time Series Models.

Everything you need to get started is contained within this book. Deep Time series Forecasting with Python is your very own hands on practical, tactical, easy to follow guide to mastery.
Buy this book today and accelerate your progress!

Table of Contents

Chapter 1 The Characteristics of Time Series Data Simplified
Chapter 2 Deep Neural Networks Explained
Chapter 3 Deep Neural Networks for Time Series Forecasting the Easy Way
Chapter 4 A Simple Way to Incorporate Additional Attributes in Your Model
Chapter 5 The Simple Recurrent Neural Network
Chapter 6 Elman Neural Networks
Chapter 7 Jordan Neural Networks
Chapter 8 Nonlinear Auto-regressive Network with Exogenous Inputs
Chapter 9 Long Short-Term Memory Recurrent Neural Network
Chapter 10 Gated Recurrent Unit
Chapter 11 Forecasting Multiple Outputs
Chapter 12 Strategies to Build Superior Models