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In machine learning, boosting is an ensemble meta-algorithm for primarily reducing bias, and also variance in supervised learning, and a family of machine learning algorithms that convert weak learners to strong ones. As for the formal definition of Machine Learning, we can say that a Machine Learning algorithm learns from experience E with respect to some type of task T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.. For example, If a Machine Learning algorithm is used to play chess. 02:01. So, if you are looking for statistical understanding of these algorithms, you should look elsewhere. According to a study, Machine Learning Engineer was voted one of the best jobs in the U.S. in 2019. 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