SKU/Artículo: AMZ-B0D9K7NKWR

Deep Learning for Recommender Systems: Techniques and Applications

Format:

Paperback

Detalles del producto
Disponibilidad:
En stock
Peso con empaque:
0.56 kg
Devolución:
Condición
Nuevo
Producto de:
Amazon
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USA

Sobre este producto
  • Unlock the full potential of deep learning to create powerful, accurate recommender systems with Deep Learning for Recommender Systems: Techniques and Applications. This comprehensive guide bridges the gap between theory and practice, offering a detailed exploration of how neural networks can be leveraged to improve recommendation accuracy across various domains.What You'll Learn:Fundamentals of Recommender Systems: Understand the history, types, and importance of recommender systems.Deep Learning Basics: Gain a solid grounding in neural networks, including CNNs, RNNs, and autoencoders.Advanced Architectures and Techniques: Dive into hybrid models, reinforcement learning, and state-of-the-art deep learning frameworks.Practical Implementation: Follow step-by-step examples and code snippets to build and train your own deep learning-based recommender systems.Case Studies and Real-World Applications: Explore detailed case studies that demonstrate the application of deep learning techniques in real-world scenarios.Future Trends and Research Directions: Stay ahead of the curve with insights into emerging technologies and future directions in the field of recommender systems.
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