In this article, I will try to cover a simple yet effective part of the math behind machine learning which is the probabilistic view of models using probability simple rules only.

How far is math important when speaking about machine learning?

Many of us start looking at the coding part to improve programming skills.

Machine learning has become a debatable field in the last 5 years, especially after the bomb of *‘Deep Learning’*. Within this wide rush towards it, it is important for any beginner in this field to understand the basics of machine learning and its core aspect, the one that is _leading _it to be here today, and the _core _that will lead **machines **to lead the world.

In this article, I will try to cover a simple yet effective part of the math behind machine learning which is the probabilistic view of models using probability simple rules only.

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The past few decades have witnessed a massive boom in the penetration as well as the power of computation, and amidst this information.

“You do not really understand something unless you can explain it to your grandmother” Not sure where this quote originally came from, it is sometimes kind of half-attributed to Albert Einstein.

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