beta distribution

Beta Distribution — Intuition, Examples, and Derivation

Towards Data Science

The Beta distribution is a probability distribution on probabilities. For example, we can use it to model the probabilities: the Click-Through Rate of your advertisement, the conversion rate of…

Beta Distributions: A Cornerstone of Bayesian Calibration

Towards Data Science

Hi there! Distributions may not seem like a complex concept at first glance, but they are incredibly powerful and fundamental in the world of data analysis and statistics. Think about it this way: if ...

Beta Distributions

Towards Data Science

Somehow, in years of schooling, I’d never heard of beta distributions until I stumbled onto them on accident over at David Robinson’s blog, but they’ve quickly become one of my favorite…

Once again, Beta Distribution

Analytics Vidhya

Long time ago I’ve been asked a question “Why is Beta distribution used in Bayes theorem” at an interview for Data Analyst position. At that time I’ve never heard of Beta Distribution therefore I…

Beta Distribution Simply Explained

Towards Data Science

A concise and easy explanation of the Beta distribution. Continue reading on Towards Data Science

Visualizing Beta Distribution and Bayesian Updating

Towards Data Science

Beta distribution is one of the more esoteric distributions compared to Bernoulli, Binomial and Geometric distributions. This post supplements intuitive understanding with visual learning.

Beta-divergence loss functions

Scikit-learn Examples

Beta-divergence loss functions A plot that compares the various Beta-divergence loss functions supported by the Multiplicative-Update (‘mu’) solver in NMF .

Python Scenario Analysis: Modeling Expert Estimates with the beta-PERT Distribution

Towards Data Science

Python scenario analysis: using the beta-PERT distribution in SciPy to model expert estimates.

Dirichlet Distribution: The Underlying Intuition and Python Implementation

Towards Data Science

The Dirichlet distribution is a generalization of the beta distribution. In Bayesian statistics, it is commonly used as the conjugate prior to the multinomial distribution, hence it can be used to mod...

Distributions

Think Bayes

In the previous chapter we used Bayes’s Theorem to solve a cookie problem; then we solved it again using a Bayes table. In this chapter, at the risk of testing your patience, we will solve it one mor...

Distributions

Dive intro Deep Learning Book

Now that we have learned how to work with probability in both the discrete and the continuous setting, let’s get to know some of the common distributions encountered. Depending on the area of machine ...

Dealing with Conversion Metrics? Consider Beta-Binomial Model

Towards Data Science

Member-only story Dealing with Conversion Metrics? Consider Beta-Binomial Model Learn a feature engineering technique to make conversion-based metrics such as CTR/CVR more representative and stable Pa...