LLM-generated summary
Josh Starmer’s illustrated guide teaches core machine-learning ideas—cross-validation, bias and variance, regression, naive Bayes, trees, and neural nets among them—through informal pictures and intuition-first explanations rather than dense linear algebra. It is a visual primer for newcomers who want to know what the algorithms are doing, not a graduate machine-learning theory text.