How to Get Started with Deep Learning for Time Series Forecasting (7-Day Mini-Course)

Last Updated on August 5, 2019

Deep Learning for Time Series Forecasting Crash Course.

Bring Deep Learning methods to Your Time Series project in 7 Days.

Time series forecasting is challenging, especially when working with long sequences, noisy data, multi-step forecasts and multiple input and output variables.

Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality.

In this crash course, you will discover how you can get started and confidently develop deep learning models for time series forecasting problems using Python in 7 days.

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Kick-start your project with my new book Deep Learning for Time Series Forecasting, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.