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In this 2-hour long project-based course, you will learn how to implement various ensemble techniques and use it in machine learning. Ensemble models in machine learning combine the decisions from multiple models to improve the overall performance, The main causes of error in learning models are due to noise, bias and variance, Ensemble methods help to minimize these factors.
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por Michael F
•22 de dic. de 2021
This project walks through basic usage of scikit-learn's ensemble models. Their use is demonstrated both as stand alone models and as layers in a heterogeneous stacking model. The presentation was perfect for me because I knew the theory behind these models but not so much the scikit-learn usage. I strongly advise reading about bagging, boosting, etc. before doing the project, if you don't already have a theoretical background.
por Ezequiel M
•24 de oct. de 2022
There was no explanation whatsoever, it was a guy sharing a screen making model.fit and printing accuracy
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