The book is split into two major sections-foundational Python programming and introductory machine learning. Readers are guided through essential concepts such as data types, variables, control flow, object-oriented programming, and using libraries like pandas for data manipulation.
In the machine learning section, topics like model selection, supervised vs unsupervised learning, bias-variance, and common algorithms are demystified with practical coding examples. It's a structured, clear roadmap to mastering both programming and applied ML from zero knowledge.
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