Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python

### Editorial Review "Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python" provides a foundational understanding of image processing and machine learning concepts. However, while the book claims to be aimed at practical applications, customer feedback suggests that it falls short in delivering substantial machine learning content. Many users appreciate the quality of the print, noting that the physical product is pleasant to handle. However, the content itself has drawn criticism for being overly simplistic, especially in the initial chapters. The first 40 pages are filled with basic Python explanations and a focus on file formats, which many readers feel is unnecessary for a text of this nature. Moreover, the repetition in the book's content—particularly in the examples—is noted as a significant flaw. Readers found that similar processes were described multiple times with only slight variations, which detracts from the overall value of the text. When the book does attempt to delve into more complex topics, it offers little elaboration, leaving readers wanting more in-depth explanations of advanced methods. The discussion surrounding prominent libraries like OpenCV, Keras, and Scikit-Learn is present, but the treatment of these subjects tends to be basic and lacks the depth that more experienced learners might seek. Additionally, many reviewers suggest that the book appears to use popular buzzwords to market itself without providing meaningful content, which may mislead readers in search of a comprehensive examination of machine learning practices. Overall, while some users commend the book for its good print quality and basic introductions to image processing, it seems better suited for complete novices in programming rather than those looking for substantial insight into machine learning applications. Many suggest seeking other resources for those already familiar with Python or looking to advance their skills. ###