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5482e3fc95f60761ffa5a764e75c203e87cf6181
start_date property (#245)
* refactor(Training): remove non-expanding window option * feat(Config): added `start_date` property * fix(Inference): added start_date here as well * fix(Linter): ran
feat(Project): use SKLearn models directly, removed custom ensembling, use 5 minute data, batch inference, numba cusum filter (#192)
Financial time series prediction
And end-to-end pipeline to train predictive Machine Learning models on financial (non-stationary, regime changing) time series. Includes feature selection and meta labelling.
Description
Languages
Python
85%
Jupyter Notebook
15%