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Deep Dive into Deep Learning with Keras and TensorFlow: Build AI Models for Computer Vision, NLP, and More - Couverture souple
Synopsis
Dive into the transformative world of artificial intelligence with Deep Dive into Deep Learning with Keras and TensorFlow: Build AI Models for Computer Vision, NLP, and More. This comprehensive guide is designed for aspiring data scientists, developers, and AI enthusiasts eager to harness the power of deep learning to tackle real-world challenges.In this essential book, you will discover:
- Foundational Knowledge: Start with an introduction to the core concepts of deep learning, including neural networks and their architectures. Understand the principles that underpin powerful models and how they relate to various applications.
- Hands-On Implementation: Engage with practical, step-by-step tutorials that guide you through building and training deep learning models using Keras and TensorFlow. From simple feedforward networks to complex convolutional neural networks (CNNs) and recurrent neural networks (RNNs), you’ll learn to implement them all.
- Real-World Applications: Explore case studies that illustrate how deep learning is applied in fields such as computer vision, natural language processing (NLP), and speech recognition. Learn how industry leaders leverage these technologies to drive innovation and efficiency.
- Advanced Techniques: Delve into advanced topics such as transfer learning, generative adversarial networks (GANs), and reinforcement learning. Understand how these cutting-edge techniques can enhance your models and expand their capabilities.
- Deployment Strategies: Learn how to deploy your models in production environments. Discover best practices for scaling applications and ensuring they perform well in real-time scenarios.
- Future Trends: Stay ahead of the curve by exploring emerging trends in AI and deep learning. Understand the implications of advancements in technology and how they will shape the future of machine learning.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
- ÉditeurIndependently published
- Date d'édition2024
- ISBN 13 9798305291513
- ReliureBroché
- Langueanglais
- Nombre de pages187
- Coordonnées du fabricantnon disponible
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