The book "Practical Machine Learning and Image Processing" offers a comprehensive introduction to the methods and algorithms of image processing using machine learning and neural networks in Python. It begins with setting up the environment and explaining fundamental concepts of image processing, followed by an exploration of relevant Python concepts that are useful for implementing the algorithms covered in the book. Readers are guided through the core algorithms of image processing and become familiar with the most significant computer vision library, OpenCV. Additionally, advanced methods of machine learning and deep learning for image processing and classification are discussed, including techniques such as Pulse Coupled Neural Networks, AdaBoost, XGBoost, and Convolutional Neural Networks. The book places particular emphasis on applying the concepts in real-world scenarios, enabling readers to apply image processing techniques and create tailored machine learning models.