The 10 Algorithms Machine Learning Engineers Need to Know

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. Some of the most common examples of machine learning are Netflix's algorithms to make movie suggestions based on movies you have watched in the past or Amazon's algorithms that recommend books based on books you have bought before. For me, my first introduction is when I took an Artificial Intelligence class when I was studying abroad in Copenhagen. Machine learning algorithms can be divided into 3 broad categories -- supervised learning, unsupervised learning, and reinforcement learning.Supervised learning is useful in cases where a property (label) is available for a certain dataset (training set), but is missing and needs to be predicted for other instances.