000			03897nam a22003017a 4500
003			OSt
005			20260824094131.0
008			260824b |||||||| |||| 00| 0 eng d
020			_a9798878584753 [paperback]
040			_aUniversity of Cebu-Banilad _cUniversity of Cebu-Banilad
100			_aAdams, Jonathan, _eauthor.
245			_aAI foundations of neural networks / _cJonathan Adams.
260			_aUSA : _bIndependently published, _cc2024.
300			_a68 pages ; _c22.7 cm.
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
505			_aContents: 1 The neuron, The fundamental unit — 2 Activation functions: Bringing neurons to life — The anatomy of layers — Backpropagation learning from errors — Loss functions measuring performance — Optimization algorithms: The road to convergence — 7 Overfitting and generalization — 8 Advanced architecture.
520			_a"Dive into the fascinating world of artificial intelligence with "AI Foundations of Neural Networks." This comprehensive guide demystifies the complex concepts of neural networks, offering a clear and accessible path to understanding the core principles that fuel modern AI systems. From the basic building blocks of neural networks to advanced architectures, this book is designed to provide a thorough grounding in deep learning for readers at all levels of expertise. Chapters Overview: The Neuron - The Fundamental Unit: Explore the basic structure that mimics the human brain's neurons, setting the stage for understanding how neural networks operate. Activation Functions - Bringing Neurons to Life: Learn about the functions that help neural networks make decisions, allowing them to process information in complex ways. The Anatomy of Layers: Delve into how layers of neurons work together to process data, forming the backbone of neural network architecture. Backpropagation - Learning from Errors: Understand the mechanism by which neural networks learn from their mistakes, optimizing their performance over time. Loss Functions - Measuring Performance: Discover how neural networks evaluate their accuracy and make adjustments to improve their predictions. Optimization Algorithms - The Road to Convergence: Get to grips with the strategies that guide neural networks towards making more accurate predictions. Overfitting and Generalization: Learn about the challenges of making models that perform well not just on the data they were trained on but on new, unseen data as well. Advanced Architectures: Explore the frontier of neural network design, including the latest models that drive progress in AI research. Why This Book? "AI Foundations of Neural Networks" stands out as a beacon of knowledge, transforming what might appear as a complex field into a series of comprehensible concepts. With a focus on clarity, practical insights, and intuitive understanding, this book bridges the gap between theoretical knowledge and real-world application. Whether you're a student, professional, or enthusiast eager to navigate the realm of AI, this guide illuminates the path forward. Embark on a journey through the corridors of deep learning with "AI Foundations of Neural Networks." Unlock the secrets behind the artificial intelligence technologies that are transforming our world. Your exploration of neural networks starts here. Perfect for: Students, AI professionals, tech enthusiasts, and anyone curious about the inner workings of neural networks and deep learning." —Provided by the publisher
521			_aAdult
541			_aPurchased _xOrtega, Eric _yCollege of Computer Studies _zComputer Science
546			_aText in English
650			_aNeural networks (Computer science).
650			_aMachine learning.
942			_2ddc _cSR
998			_cGian [new] _d08/24/2026
999			_c15603 _d15603