practical guides deep neural network von continental academy press (3 Ergebnisse)

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Deep neural networks have revolutionized the field of artificial intelligence, enabling developers to build sophisticated models that learn from complex data. 'Practical Guides to Deep Neural Network Design' offers a comprehensive exploration of the key strategies and techniques required to design and deploy deep neural networks. By examining the intricacies of neural network architecture and training algorithms, this book provides actionable insights into building efficient, effective, and scalable deep learning models. With its data-driven approach and real-world examples, 'Practical Guides to Deep Neural Network Design' is an indispensable resource for developers seeking to harness the power of deep learning and unlock the full potential of their AI applications. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Practical Guides to Deep Neural Network Design presents a structured approach to constructing effective neural architectures. The book covers foundational concepts, layer configurations, and training methodologies that influence model performance. It emphasizes the importance of experimentation and fine-tuning to achieve optimal results in complex tasks. This guide aims to assist practitioners in designing deep learning models that are both efficient and accurate across diverse applications. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Practical Guides to Deep Neural Network Design presents a hands-on approach to constructing advanced neural architectures. This book explores various design principles, layer configurations, and training techniques to develop effective deep learning models. It emphasizes real-world applications, model optimization, and scalability considerations. Readers will find detailed explanations of neural network components, enabling the creation of robust AI systems tailored to complex problems across diverse domains. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.