Dive into a comprehensive tutorial on solving real-world computer vision problems using Python and convolutional neural networks (CNNs). Learn to create and improve models for flower classification, specifically distinguishing "La Eterna" from other types. Explore Tensorflow/Keras libraries to build simple and advanced CNN architectures, implement data augmentation and preprocessing techniques, and utilize Keras Tuner for optimizing network structures. Gain insights on the importance of precision and recall versus accuracy in model evaluation. Follow along with provided code examples, dataset exploration, and step-by-step explanations of CNN concepts and implementation strategies.