Ensemble Learning, Bootstrap Aggregating (Bagging) and Boosting

#EnsembleLearning #EnsembleModels #MachineLearning #DataAnalytics #DataScience

Ensemble Learning is using multiple learning algorithms at a time, to obtain predictions with an aim to have better predictions than the individual models.

Ensemble learning is a very popular method to improve the accuracy of a machine learning model.
It avoid overfitting and gives us a much better model.
bootstrap aggregating (Bagging) and boosting are popular ensemble methods.

In the next tutorial we will implement some ensemble models in scikit learn.
For all Ipython notebooks, used in this series : https://github.com/shreyans29/thesemicolon
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