Coding Challenge 187 - Bayes Theorem

Learn to implement a Naive Bayes text classifier from scratch in JavaScript using p5.js in this comprehensive coding tutorial. Explore the mathematical foundations of Bayes' theorem and understand how it applies to text classification problems. Build a complete sentiment analysis system that analyzes word frequencies, implements Laplacian smoothing to handle unseen words, and creates probability calculations for classification decisions. Follow along as the implementation progresses from basic setup through advanced features like normalization techniques and user interface development. Master key machine learning concepts including training data processing, probability distribution calculations, and smoothing algorithms while creating a fully functional text classifier that runs entirely in the browser. Access multiple working code examples and interactive p5.js sketches to experiment with different approaches to Bayesian classification, from initial implementations to refactored versions with file loading capabilities.