The Foundations of Deep Learning: From Logic to AI

“The Foundations of Deep Learning: From Logic to AI” serves as a comprehensive guide bridging the gap between the theoretical underpinnings and practical applications of deep learning. The book illuminates the core concepts of deep learning, unraveling the intricate workings of neural networks. From the basics of pattern recognition to the complexities of natural language processing, it navigates through the diverse applications that form the backbone of modern AI.

A special focus is dedicated to autoencoders, shedding light on their role in unsupervised learning and data representation. By tracing the journey from logic to the expansive landscape of artificial intelligence, this book offers a holistic perspective on the foundations of deep learning. Whether you are a novice eager to grasp the fundamentals or an experienced practitioner seeking deeper insights, this resource provides a nuanced understanding of the logic-driven evolution that underlies the transformative field of deep learning.

Keywords

Deep learning, Neural networks, Pattern recognition, Natural language processing, Autoencoders