ML Algorithms Made Simple – Bagging & Boosting

This is part of my answer to interview question 9 which is to explain your favorite machine learning algorithm in five minutes.

Bagging & Boosting Made Simple

Bagging and boosting are two different types of ensemble learners.  Ensemble learning is a method of combining many weak learners together to build a more complex learner.  This is also called ‘meta-learner’ because ensemble learners combine other types of learners to get a final output.  A weak learner is simply any learner that does better than random chance.

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Machine Learning Basics – A Quick Guide

Machine learning, you have heard that term by now, but what does it actually mean?  What is machine learning? How does a machine actually learn something?  What can you do with machine learning?

This post will help you get a basic understanding of what machine learning is and how it works.  I will explain the various ways it is currently used and describe the basic types of machine learning algorithms.

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