Neural Networks for Beginners
Daniel Huston
Neural Networks for Beginners
Daniel Huston
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"Neural Networks for Beginners" is a beginner-friendly guide to understanding the basics of neural networks, machine learning, and deep learning. Written in simple language, this book provides a comprehensive introduction to the key concepts and techniques used in neural networks.
Starting with an overview of the history and importance of neural networks, the book covers the basics of machine learning and deep learning, including their differences and applications. It then delves into the different types of neural networks, their architectures, and how they are trained and optimized.
The book also provides real-world examples of successful neural network applications in various fields, such as healthcare, finance, and technology. It explains how neural networks are used in practical applications, such as image recognition, speech recognition, and natural language processing.
"Neural Networks for Beginners" is perfect for anyone with no prior knowledge of neural networks who wants to learn about this exciting field. Whether you are a student, researcher, or professional, this book will provide you with the knowledge and skills needed to get started with neural networks. With this book, you'll gain a solid understanding of the basics of neural networks and be prepared to explore and leverage their power.
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