In this article, we will be using the Pomegranate library to build a simple Hidden Markov Model

The HHM will be based on an example from the book Artificial Intelligence: A Modern Approach:

You are the security guard stationed at a secret under-ground installation. Each day, you try to guess whether it’s raining today, but your only access to the outside world occurs each morning when you see the director coming in with, or without, an umbrella.

A simplified diagram of the required network topology is shown below.

Describing the Network

lambda = (A, B) specifies a Hidden Markov Model in terms of…


In this article, I would like to show how a simple algorithm such as naive Bayes can actually produce significant results. I will go through the algorithm in a real dataset and explaining every step in the preprocessing of the text to the pros/cons of the algorithm.

Naive Bayes algorithm applies probabilistic computation in a classification task. This algorithm falls under the Supervised Machine Learning algorithm, where we can train a set of data and label them according to their categories.

You can see my article and code on my blog as well!

What we want to achieve

We will be using Naive Bayes to…


The Donuts Code

The spinning “donuts” has brought some attention recently and was created by the amazing Andy Sloane. No wonder, a flying donut on your terminal? You can find the code below in c. The “pixels” are ASCII characters .,-~:;=!*#$@ that accounts for the illumination value of the surface, but I'll explain step by step below along with the math.

You can follow this article on my blog on AI/Data Science

Mission:

Steps

  1. Create a circle of radius R2 centred at R2

Monique Marins

Data Scientist, passionate about data storytelling.

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