Investigate Anomalies in Temporal Data With Machine Learning

Investigate Anomalies in Temporal Data With Machine Learning

Use Python and Machine Learning to analyze time-series data and visualize it interactively. We will be exploring Facebook’s open-source SARIMA model Prophet to identify outliers in time-series data.

Here’s what you’ll be making:

Overview

In this notebook, we will be exploring Facebook’s open-source SARIMA model Prophet to identify outliers in time-series data. Here’s what you’ll learn:

  • What is time-series data?
  • What is SARIMA?
  • Build a simple optimizer to auto-optimize the Prophet model
  • How to use Prophet to forecast data
  • Use Prophet and Bokeh to identify outliers in an interactive dashboard
  • Use Bokeh to create a time-series dashboard layout for investigation

time data-visualization data-science dashboard machine-learning

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