Overview of machine learning algorithms

machine learning algorithms

A few years ago, machine learning caught my attention, and since then, my interest in this field keeps growing. Every day we see more and more intelligent solutions surrounding us. You probably noticed that shopping sites adapt to our interests and suggests targeted offers; another example is spam email filters; if we mark emails as spam, they keep disappearing from our lives. Another area is robotics, where they learn how to navigate independently and perform various tasks. Machine learning algorithms cover autonomous flying robots, helicopters, quads, handwriting recognition, computer vision, data mining, and multiple fields like markets, biomedicine, biology – all this.  Here are a few reasons why machine learning is significant and sometimes necessary: Data mining. Sometimes it isn’t possible to understand the nature data and relations between them so that machine learning algorithms can extract these hidden relations. Adaptation. It is hard to design a flexible algorithm that could adapt to a changing environment. Machine learning algorithms can be used to improve themselves according to changing data. Scale. There can be much knowledge in data sets that sometimes aren’t completely understood by a human designer. Machine learning algorithms can learn from this knowledge without human interaction. Complexity. The…

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