Easy-to-use box ML solution for forcasting consumption
Project description
What is this Library about?
Easy-to-use (4 lines of code, actually) framework for training powerful predictive models!
Description
We made a mother-model, which consists of multiple layers of predictive models: ewma is used as trend, Prophet is used for getting seasonality, CatBoost is used for predicting residuals. Why did we do that? Because we needed a out-of-the-box solution, which could be used by non-ML users.
Maintained by
Library is developed and being maintained by Teremok ML team
Contacts
Our website: https://teremok.ru/ ML team: you can contact us via telegram channel @pivo_txt
Change Log
0.1.0 (27.07.2024)
- First release
1.1.0 (28.07.2024)
- Beta verison release
- Visualisation of itertest added
1.1.1 (06.08.2024)
- Fixed some bugs
Release history Release notifications | RSS feed
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