Dominoes (more importantly, numbers).
Bayesian statistics
Feb 22, 2021 | 10 min read

Bayesian Inference for the Normal Model

The normal distribution has two parameters, but we focus on the one-parameter setting in this lecture. We also introduce the posterior predictive check as a way to assess model fit, and briefly discuss the issue with improper prior distributions.

The lottery.
Bayesian statistics
Feb 15, 2021 | 8 min read

Monte Carlo Sampling

This lecture discusses Monte Carlo approximations of the posterior distribution and summaries from it. While this might not seem entirely useful now, this underlies some of the key computational methods used for Bayesian inference that we will discuss further.

Superman logo.
Data mining
Feb 12, 2021 | 4 min read

Logistic Regression

In linear regression, the function learned is used to estimate the value of the target $y$ using values of input $x$. While it could be used for …

Grand Canyon National Park, United States.
Data mining
Feb 11, 2021 | 6 min read

Gradient Descent and Linear Regression

We implement linear regression using gradient descent, a general optimization technique which in this case can find the global minimum.

A magazine stand in Kiev, Ukraine.
Data mining
Feb 9, 2021 | 12 min read

Text Classification with Naive Bayes and NLTK

In the last post we talked about the theoretical side of naive Bayes in text classification. Here we will implement the model in Python, both from …

Solheimasandur plane wreck, Iceland.
Bayesian statistics
Feb 8, 2021 | 8 min read

Bayesian Inference for the Poisson Model

This lecture discusses Bayesian inference for the Poisson model, including conjugate prior specification, a different way to specify a "non-informative" prior, and relevant posterior summaries.

@markuswinkler from Unsplash.
Data mining
Feb 3, 2021 | 7 min read

Naive Bayes

We talk about one of the simplest classification methods, naive Bayes classifiers, and its applications in text classification. It's not really machine learning as we only need a single pass through the data to compute necessary values.

Person working on a test.
Bayesian statistics
Jan 25, 2021 | 18 min read

Bayesian Inference for the Binomial Model

The general procedure for Bayesian analysis. We use two different prior models and compare the resulting posteriors (visually and mathematically).

An iPhone under repair.
Bayesian statistics
Jan 18, 2021 | 11 min read

Frequentist Inference

A simple problem in the binomial setting solved under the frequentist view of statistics.

Bookstore in Warsaw, Poland.
Bayesian statistics
Jan 13, 2021 | 6 min read

Introduction to Bayesian Statistics

First lecture of the course, and a brief history of Bayesian statistics.