This textbook provides a comprehensive, code-first introduction to Artificial Intelligence and Machine Learning (AIML). Bridging the gap between mathematical theory and practical execution, it guides readers through 12 structured chapters covering data preprocessing, classical machine learning algorithms, and advanced deep learning architectures like CNNs, RNNs, and Autoencoders. Every concept is backed by rigorous mathematical foundations and fully realized through step-by-step Python implementations.

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