You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
ML-For-Beginners/7-TimeSeries
Vishvanathan K adf07f636f
Changed pip to !pip
3 years ago
..
1-Introduction fixes 3 years ago
2-ARIMA Changed pip to !pip 3 years ago
images re-numbering lesson groups 3 years ago
translations Link fix 3 years ago
README.md fixes 3 years ago

README.md

Introduction to time series forecasting

What is time series forecasting? It's about predicting future events by analyzing trends of the past.

Regional topic: worldwide electricity usage

In these two lessons, you will be introduced to time series forecasting, a somewhat lesser known area of machine learning that is nevertheless extremely valuable for industry and business applications, among other fields. While neural networks can be used to enhance the utility of these models, we will study them in the context of classical machine learning as models help predict future performance based on the past.

Our regional focus is electrical usage in the world, an interesting dataset to learn about forecasting future power usage based on patterns of past load. You can see how this kind of forecasting can be extremely helpful in a business environment.

electric grid

Photo by Peddi Sai hrithik of electrical towers on a road in Rajasthan on Unsplash

Lessons

  1. Introduction to time series forecasting
  2. Building ARIMA time series models

Credits

"Introduction to time series forecasting" was written with by Francesca Lazzeri and Jen Looper