This book is intended for developers who want to incorporate machine learning into their projects or delve deeper into the technical aspects of the field. It explores the fundamental algorithms that have made machine learning a critical area of technological innovation, with a special focus on neural networks. Multi-layer architectures, are highlighted for their essential role in modern machine learning applications, enabling complex data representations and powering advancements in areas such as content generation, language processing, and machine translation. The book balances theoretical concepts with practical implementations, providing readers with a solid understanding of how these algorithms work and how they can be applied in real-world scenarios. The text offers a thorough theoretical overview paired with step-by-step implementation guides, including C++ examples, to help readers build and apply neural network architectures effectively across various problem domains. Practical examples encourage hands-on learning, fostering a deep understanding of the principles and dynamics of machine learning algorithms.