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GitHub / IDB-FOR-DATASCIENCE / Predictive-Excellence-Engine

In this notebook, we will create an AI and time serie driven forecasting engine based on a set of 5 AI models and 5 time series models and employ several algorithms to perform feature engineering and selection on a multivariate time series dataset.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IDB-FOR-DATASCIENCE%2FPredictive-Excellence-Engine

Stars: 11
Forks: 3
Open Issues: 0

License: mit
Language: Jupyter Notebook
Repo Size: 1.31 MB
Dependencies: 0

Created: over 3 years ago
Updated: 6 months ago
Last pushed: almost 3 years ago
Last synced: 4 months ago

Commit Stats

Commits: 6
Authors: 1
Mean commits per author: 6.0
Development Distribution Score: 0.0
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/IDB-FOR-DATASCIENCE/Predictive-Excellence-Engine

Topics: forecasting, lstm, sarimax, timeseries, var, vecm, xgboost

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