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Pluralsight

Implement Time Series Analysis, Forecasting and Prediction with Tensorflow 2.0

via Pluralsight

Overview

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Time series analysis is one of the more difficult and confusing aspects of data science. This course will teach you how to use TensorFlow with time series data and
generate high performing forecasts and predictions.

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.

Syllabus

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

Taught by

Chase DeHan

Reviews

2.6 rating at Pluralsight based on 36 ratings

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