Naive Bayes. This is a supervised machine learning classification technique that uses Bayes’ theorem to make classification predictions. Today I worked through a simple example of the technique and also found this explainer of Bayes’ theorem especially useful, along with an explanation by ChatGPT4.
In machine learning Navie Bayes comes in a variety of types. The simplest one—multinomial naive bayes—is especially useful when you have discrete data. The example in this book is a fantastic place to start, and it’s what I used to grasp the concept, with a simple email spam filter that uses the probability of words in regular messages versus spam, to make predictions about whether a specific email is spam or not.
I’m currently 45% of the way through this book and will continue tackling a chapter at a time, while also doing python workouts to keep my coding knowledge tight.