**WHY STRUGGLE?**

Why spend five hours ploughing through technical equations, proofs and lemmas when the core idea can be explained in ten minutes and deployed in fifteen? I wrote this book because I don't want you to spend your time struggling with the mechanics of implementation or theoretical details.

**Deep Time Series Forecasting with Python**presents the algorithms in a way that I wish I had access to when I was starting out. Even if you've never attempted to forecast anything, you can easily make your computer do the grunt work. This book will teach you how to apply the very best Python tools to solve basic time series problems.

**LEARN IN HALF THE TIME!**

This book 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 neural network forecasting models using Python. If you’re a working professional, economist, business analyst or just interested in trying out new machine learning ideas, you will learn the basics of deep learning for time series forecasting, and get to play with some cool tools. Once you have mastered the basics, you will be able to use your own time series data to effortlessly forecast the future.

**TAKE THE SHORTCUT**

Also, almost all advice on machine learning for time series forecasting comes from academics; this comes from a practitioner. My personal experience with neural networks is that everything became much clearer when I started ignoring full-page, dense derivations of backpropagation equations and just started using them to solve real world problems.

**• 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.

• 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.

**DO YOU WANT PRACTICAL REAL WORLD EXAMPLES USING PYTHON?**

**YES!**Then

**Deep Time Series Forecasting with Python**is for you. This hands on text is designed for individuals who want to learn how to use neural networks for time series forecasting in the minimum amount of time. It leverages the power of the Python programming language to provide you with the necessary tools to maximize your understanding, deepen your knowledge and unleash ideas to enhance your data analysis projects.

Tell Me More!

**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**

**This is an exciting time to be involved in Data Science.**

**Buy Today and Join the Data science Revolution!**