Explained boosting and bagging algorithm in simple layman terms and explained their differences in plain English — Bagging and boosting are two commonly used techniques today in machine learning. While both of them are intended to improve the performance of a machine learning model, operationally they are very different and they have their own pros and cons. The question that we are trying to address here is…

A deep dive into performance metrics for Machine learning models for classification models and selecting the best metric based on business scenario — Metrices play an important role in determining the performance of a machine learning model. Even more important use case of metrices is to benchmark and report the performance across board. There is a large set of metrics available to chose from, but pertaining to one’s business problem, it becomes critical…