A live coding session implementing a Naive Bayes spam classifier in Go from scratch. The implementation covers tokenization, bag-of-words representation, probability calculations using Bayes' theorem, and training on a public email dataset. The session demonstrates handling numerical underflow with logarithmic probabilities and
•2h 16m watch time
Sort: