Likelihood, Probability, and the Math You Should Know

<p>Likelihood is a confusing term. Likelihood is not a probability, but is proportional to a probability; the two terms can’t be used interchangeably. In this post, we will be dissecting likelihood as a concept and understand it’s importance in machine learning.</p> <h1>Intuition</h1> <p>Let us understand likelihood and how it is different from a probability distribution with an imaginary city, Databerg (a cringe name, but bear with me). Let’s also imagine we have access to the pricing data of all houses in this city. I don’t know exactly how this distribution looks since Databerg isn’t a real city, but intuitively I’d say we would notice many houses that are moderately priced and a few houses that are very expensive. If one were to plot a distribution of these prices, it might look something like this.</p> <p><a href="https://towardsdatascience.com/likelihood-probability-and-the-math-you-should-know-9bf66db5241b"><strong>Read More</strong></a></p>