000			04654nam a22003137a 4500
003			OSt
005			20260924104839.0
008			260824b |||||||| |||| 00| 0 eng d
020			_a9798328003285 [paperback]
040			_aUniversity of Cebu-Banilad _cUniversity of Cebu-Banilad
100			_aShin, Kilho, _eauthor.
245			_aDeep learning demystified : _ba step-by-step introduction to neural networks / _cKilho Shin.
260			_aUSA : _bIndependently published, _cc2024.
300			_avii, 85 pages : _billustrations (black & white) ; _c22.8 cm.
336			_2rdacontent _atext
337			_2rdamedia _aunmediaetd
338			_2rdacarrier _avolume
505			_aContents: Chapter 1: Introduction to artificial neural networks and perceptrons — Chapter 2: Neurons and artificial neurons — Chapter 3: Perceptron learning algorithm — Chapter 4: Limitations of perceptron and multi-layer neural networks — Chapter 5: Activation functions — Chapter 6: Gradients descent — Chapter 7: Backpropagation algorithm — Chapter 8: Applications of neural networks.
520			_a""Deep Learning Demystified: A Step-by-Step Introduction to Neural Networks" is a comprehensive guide designed to make the world of artificial neural networks accessible and engaging. With a focus on simplicity and clarity, this book offers readers an easy-to-follow journey through the fascinating field of deep learning, without requiring an extensive background in mathematics or programming. Ever since the concept of Artificial Intelligence (AI) emerged, humans have dreamed of creating machines that can think and communicate like us. This dream is now becoming a reality through the advancements in AI, particularly with machine learning and deep learning. At the core of these technologies are Artificial Neural Networks (ANNs), which mimic the structure and function of the human brain to process and learn from data. In this book, you will embark on a journey that begins with the basics of neural networks and perceptrons, and gradually progresses to more advanced concepts and applications. Each chapter is meticulously crafted to build your understanding step-by-step, ensuring you grasp the foundational principles before moving on to complex topics. Key Topics Covered: Chapter 1: Introduction to Artificial Neural Networks and Perceptrons Explore the dream of AI and understand the basic concepts of neural networks. Chapter 2: Neurons and Artificial Neurons Dive into the structure and function of biological neurons and their artificial counterparts. Chapter 3: Perceptron Learning Algorithm Learn about the learning process of neural networks with practical examples in Python. Chapter 4: Limitations of Perceptron and Multi-Layer Neural Networks Discover the limitations of single-layer perceptrons and the rise of multi-layer networks. Chapter 5: Activation Functions Understand the role of activation functions and their various types, including Sigmoid, ReLU, and more. Chapter 6: Gradient Descent Delve into the gradient descent algorithm, its mathematical foundation, and its application in training neural networks. Chapter 7: Backpropagation Algorithm Learn about the backpropagation algorithm, a critical component in the training of deep neural networks. Chapter 8: Applications of Neural Networks Explore real-world applications of neural networks in image recognition, speech recognition, and natural language processing. Each chapter is rich with examples, illustrations, and practical insights, making complex topics understandable and enjoyable. Whether you are a student, a professional, or simply someone with a keen interest in AI, this book is your gateway to understanding and harnessing the power of neural networks. Join Kilho Shin, an AI Engineer with a passion for teaching complex topics in an easy and engaging way, as he guides you through this exciting field. With a PhD from the University of Southern California, Kilho brings a wealth of knowledge and experience to this book, ensuring that you not only learn but also enjoy the process. Embrace the future of AI with "Deep Learning Demystified" and start your journey towards mastering neural networks today." —Provided by the publisher
521			_aAdult
541			_aPurchased _xOrtega, Eric _yCollege of Computer Studies _zComputer Science
546			_aText in English
650			_aDeep learning (Machine learning).
650			_aNeural networks (Computer science).
650			_aArtificial intelligence.
942			_2ddc _cSR
998			_cGian [new] _d08/24/2026
999			_c15604 _d15604