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A to Z of Deep Learning and AI by Laith Abualigah ISBN 9781003516385, 003516386 instant download

  • SKU: EBN-238679894
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Instant download (eBook) A to Z of Deep Learning and AI after payment.
Authors:Laith Abualigah
Pages:216 pages
Year:2025
Edition:1
Publisher:Science Publishers
Language:english
File Size:1.89 MB
Format:pdf
ISBNS:9781003516385, 003516386
Categories: Ebooks

Product desciption

A to Z of Deep Learning and AI by Laith Abualigah ISBN 9781003516385, 003516386 instant download

The book unravels fundamental concepts that underpin deep learning, allowing even those without prior technical knowledge to grasp the intricacies of neural networks and machine learning algorithms. It provides roadmap to understanding the key principles, from the simplest perceptron to the most advanced convolutional and recurrent networks, explaining how they can perceive, learn, and make intelligent decisions. Real-world applications of deep learning and AI are given, showcasing how these technologies have transformed industries such as healthcare, finance, and self-driving cars. Case studies and expert insights provide valuable perspectives on the enormous potential and ethical challenges in the field. The book bridges the gap between theoretical concepts and practical implementation. It empowers readers to embark on their own AI journeys, with step-by-step guidance on building and training neural networks, working with popular frameworks, and handling big data. As the AI and deep learning landscape evolves rapidly, this book keeps pace. It delves into emerging trends such as generative adversarial networks (GANs), reinforcement learning, and the ethical considerations surrounding AI development. An essential reading for AI enthusiasts, students, and professionals alike. It provides the knowledge and tools to harness the potential of intelligent machines and contribute to the ongoing AI revolution. This book demystifies deep learning and AI, making complex concepts accessible to all readers. It blends theory with practical guidance, covering neural networks, real-world applications, and ethical considerations. With insights on GANs and reinforcement learning, it empowers to build intelligent systems and drive innovation.
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