Build Your Own Neural Networks, Step-By-Step Explanation For Beginners, Shin K., 2024

Build Your Own Neural Networks, Step-By-Step Explanation For Beginners, Shin K., 2024.
     
    "Build Your Own Neural Networks: Step-By-Step Explanation For Beginners" is designed to demystify the complexities of neural networks for those who are new to the field of deep learning. This book is your comprehensive guide to understanding and implementing neural networks from the ground up, using the PyTorch framework. Each chapter is structured to provide hands-on experience with practical code examples, detailed step-by-step explanations, and engaging mini-projects that ensure a practical understanding of the concepts discussed. This approach not only enhances learning but also makes the journey fun and interactive. By avoiding complex jargon and focusing on clear, simple explanations, we ensure that you gain a solid foundation in neural networks without feeling overwhelmed.




What is a Neural Network.
In the world of artificial intelligence, neural networks take a central stage. But what are they?

Neural networks are a category of machine learning algorithms designed based on the human brain structure. They are composed of numerous 'neurons’ or 'nodes' that work together to process and analyze data. Just as biological neurons transmit information to others through synapses, the 'neurons’ or 'nodes’ in the network communicate with each other to make sense of the input data.

Consider this: our brains consist of approximately 86 billion neurons connected by trillions of synapses, which enable us to work, play, and even read this book. If we can recreate this complex and intricate system to analyze data and learn from that data, we could accomplish astounding results. With neural networks, there lies the promise of creating machines that can learn from experience, the possibility of automated learning, and the potential for machines that can improve over time, much like how humans do!

CONTENTS.
About This Book.
Who This Book Is For.
Author's Note.
Chapter 1: Introduction to Neural Networks.
Chapter 2: Setup and Installation.
Chapter 3: Numpy for Neural Networks.
Chapter 4: Building Blocks of Neural Networks.
Chapter 5: Designing Your First Neural Network.
Chapter 6: Advanced Neural Network Design.
Chapter 7: Convolutional Neural Networks.
Chapter 8: Recurrent Neural Networks.
Chapter 9: Deploying a Neural Network Model.
Chapter 10: Keeping Up With Neural Network Trends.



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