Time series predictions are difficult and the rise of neural networks and TensorFlow has made generating highly performant machine learning models possible. In this course, Implement Time Series Analysis, Forecasting, and Prediction with TensorFlow 2.0, you’ll learn how to build models with multiple TensorFlow model types and be able to select the highest performing model. First, you’ll explore time series cross validation and how to create a baseline. Next, you’ll discover how to use neural networks on a single step ahead process. Finally, you’ll learn how to expand the modeling technique to predict multiple time periods in advance along with generating multiple simultaneous predictions on different series. When you’re finished with this course, you’ll have the skills and knowledge of TensorFlow needed to build models for good time series predictions.
Author Name: Chase DeHan
Author Description:
Chase is currently Lead Data Scientist at Tesorio and formerly was an Assistant Professor of Finance and Economics at the University of South Carolina Upstate. He holds a BS, MS, and PhD, all in Economics, from the University of Utah. Prior to graduate school, Chase served two combat tours to Iraq with the US Marine Corps and competed in the 2010 Winter Olympic Trials in Bobsled. Chase is passionate about building automated machine learning systems and is a regular speaker at academic and pra… more

Table of Contents

• Course Overview
  1min
• Understanding Time Series Data
  14mins
• Building a Baseline Model
  20mins
• Utilizing Neural Networks
  13mins
• Expanding the Modeling Approach
  15mins