ML-For-Beginners/translations/pcm/7-TimeSeries

Introduction to time series forecasting

Wetin be time series forecasting? Na to sabi wetin go happen for future by to study how tins take happen for past.

Regional topic: worldwide electricity usage ✨

For dis two lessons, dem go introduce you to time series forecasting, one kain small area for machine learning wey many no sabi, but e get plenty value for industry and business and oda fields dem. Even though neural networks fit help make these models beta, we go study dem for classical machine learning way as models dey help predict how tins go be for future based on wetin happen for past.

Our regional focus na how people dey use electricity for di world, dis na better dataset to learn how to forecast how power go dey for future based on how people take use am for past. You fit see how dis kain forecasting fit really help for business environment.

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
3. Building Support Vector Regressor for time series forecasting

Credits

"Introduction to time series forecasting" na ⚡️ Francesca Lazzeri and Jen Looper write am. Di notebooks first show for online for Azure "Deep Learning For Time Series" repo wey Francesca Lazzeri na di original writer. Di SVR lesson na Anirban Mukherjee write am.

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Disclaimer: Dis document don translate wit AI translation service Co-op Translator. Even tho we dey try make am correct, abeg make you know say automated translation fit get errors or mistakes. Di original document for dia own language na im be di correct source. For important info, make person wey sabi human translation do am. We no go responsible for any misunderstanding or wrong understanding wey fit happen because of dis translation.