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30 lines
2.6 KiB
30 lines
2.6 KiB
# Introduction to time series forecasting
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Wetin be time series forecasting? Na di way wey dem dey predict wetin go happen for future by check di trend wey don happen for past.
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## Regional topic: worldwide electricity usage ✨
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For dis two lessons, you go sabi wetin time series forecasting be, one area for machine learning wey no too popular but e still dey very useful for industry and business work, plus other areas. Even though neural networks fit help make dis models better, we go study am for di classical machine learning way, as di models dey help predict wetin go happen for future based on wetin don happen for past.
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Di regional focus na di electricity usage for di world, one kind dataset wey dey interesting to take learn how to forecast di power wey people go use for future based on di pattern of di load wey dem don use before. You go see as dis kind forecasting fit dey very useful for business work.
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Photo by [Peddi Sai hrithik](https://unsplash.com/@shutter_log?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) of electrical towers on a road in Rajasthan on [Unsplash](https://unsplash.com/s/photos/electric-india?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText)
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## Lessons
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1. [Introduction to time series forecasting](1-Introduction/README.md)
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2. [Building ARIMA time series models](2-ARIMA/README.md)
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3. [Building Support Vector Regressor for time series forcasting](3-SVR/README.md)
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## Credits
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"Introduction to time series forecasting" na work wey dem write with ⚡️ by [Francesca Lazzeri](https://twitter.com/frlazzeri) and [Jen Looper](https://twitter.com/jenlooper). Di notebooks first show online for di [Azure "Deep Learning For Time Series" repo](https://github.com/Azure/DeepLearningForTimeSeriesForecasting) wey Francesca Lazzeri originally write. Di SVR lesson na work wey [Anirban Mukherjee](https://github.com/AnirbanMukherjeeXD) write.
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---
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<!-- CO-OP TRANSLATOR DISCLAIMER START -->
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**Disclaimer**:
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Dis dokyument don use AI translation service [Co-op Translator](https://github.com/Azure/co-op-translator) do di translation. Even though we dey try make am accurate, abeg make you sabi say automated translations fit get mistake or no dey correct well. Di original dokyument for im native language na di main source wey you go trust. For important information, e better make professional human translation dey use. We no go fit take blame for any misunderstanding or wrong interpretation wey fit happen because you use dis translation.
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<!-- CO-OP TRANSLATOR DISCLAIMER END --> |