Ensemble Techniques in Machine Learning

The bias-variance trade-off is a challenge we all face while training machine learning algorithms. Ensemble methods improve model precision by using a group (or "ensemble") of models which, when combined, outperform individual models when used separately. Different methods could be used to reduce variance or bias.
In this DataHour, Ritika will deeply explain the methods of ensembling machine learning models and their working.
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