As the title implies, the book provides very good coverage of essential data science and machine learning methods. The language of the book is very clear, giving readers an intuitive understanding of the concepts without the burden of heavy technical details. In less than 180 pages, the book introduces readers to statistics, probability, and the basics of how machine learning and deep learning work. It ends with contemporary subjects such as large language models (LLMs) and trustworthy artificial intelligence (AI).

The authors are very knowledgeable and do an excellent job of introducing important concepts. The book includes many helpful examples that make complex topics easier to follow. It explains key ideas like supervised learning, neural networks, and model evaluation in an accessible way. I especially like how it connects theory to real-world applications. While the book avoids deep math, it still gives readers a strong foundation.

Just enough data science and machine learning is a joy to read. I recommend it for a broad audience, regardless of background or prior knowledge of the matter.