Author(s): Egor Howell
Originally published on Towards AI.
Understanding the basic building blocks of the binomial distribution
Photo by Chris Briggs on Unsplash
The binomial distribution is a widely used statistical distribution that Data Scientists should be familiar with, as it appears in numerous contexts. One notable example is its application in supervised learning problems for classification, where the loss function, the cross-entropy loss, is derived from the binomial distribution. In this post, we will explore the intuition, theory, and examples associated with this distribution.
The binomial distribution is a discrete distribution that measures the likelihood of achieving a specific number of successes in a given number of trials. For instance, it can answer the questions “What is the… Read the full blog for free on Medium.
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Published via Towards AI