There is a significant discussion around the effectiveness and relevance of traditional machine learning textbooks, particularly regarding their theoretical focus versus practical applications. The recommendations express a preference for resources that simplify complex ideas, such as Josh Starmer's 'The StatQuest Illustrated Guide to Machine Learning.' However, criticisms indicate that many traditional sources, including older texts targeted at statistical learning theory from around 2014, may be considered outdated. The conversation reflects a broader truth about the field: practical implementations and engineering have taken precedence over theoretical formulations, highlighting a disconnect in how machine learning is often taught versus what is needed in practice. Critics emphasize that effective learning should not only concentrate on mathematical theory but also prioritize hands-on experience and applications in current technologies like neural networks and generative AI.