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AI Engineering: Building Applications with Foundation Models
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Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications.
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Ce qui se démarque
Détails du produit
| Publisher | O'Reilly Media |
| Publication date | January 7, 2025 |
| Edition | 1st |
| Language | English |
| Print length | 532 pages |
| ISBN-10 | 1098166302 |
| ISBN-13 | 978-1098166304 |
| Item Weight | 2.05 pounds (930 grams) |
| Dimensions | 6.9 x 1.1 x 9 inches (17.5 x 2.8 x 22.9 cm) |
À qui est-ce destiné ?
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Data Scientists
Ideal for data scientists looking to integrate advanced AI features into their applications using foundation models.
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Software Developers
Great for software developers who want to enhance their programming skills with artificial intelligence capabilities.
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AI Enthusiasts
Perfect for AI enthusiasts eager to learn about building applications that leverage the latest foundation models in AI.
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Beginners Without Background
Not suitable for absolute beginners in programming or AI who lack foundational knowledge.
DESCRIPTION DU PRODUIT
AI Engineering: Building Applications with Foundation Models
Questions et réponses des clients
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question:
What is 'AI Engineering: Building Applications with Foundation Models' about?
répondre: This book serves as a comprehensive guide to understanding and building applications using foundation models in AI. It covers the principles of AI engineering, methodologies for leveraging foundation models, and practical examples of applying these technologies in real-world scenarios. Readers gain insights into the architectural design, integration techniques, and deployment strategies that can help them succeed in developing AI-driven solutions. -
question:
Who is the target audience for this book?
répondre: The primary audience for this book includes software engineers, data scientists, AI researchers, and technology students interested in deep learning and AI applications. Additionally, professionals in various industries looking to implement AI solutions will find this resource invaluable. By providing practical insights and industry best practices, the book empowers readers to harness the potential of foundation models effectively. -
question:
What are foundation models and why are they important?
répondre: Foundation models are large-scale machine learning models pre-trained on diverse datasets, capable of performing a variety of tasks with limited fine-tuning. Their importance lies in their versatility and efficiency, enabling developers to build sophisticated AI applications without starting from scratch. By understanding foundation models, readers can leverage state-of-the-art technology in areas such as natural language processing, computer vision, and more, drastically reducing time-to-market for new AI solutions. -
question:
What programming languages are discussed in this book?
répondre: While the book primarily focuses on the concepts of AI engineering, it extensively covers programming in Python, which is widely used in AI and machine learning. Additionally, readers may encounter references to other languages such as R for data analysis and JavaScript for web development. The integration of diverse programming languages provides a well-rounded understanding of how to implement foundation models across different platforms. -
question:
Are there any practical examples included in the book?
répondre: Yes, the book is rich in practical examples and case studies that illustrate the application of foundation models across various industries. Every chapter includes hands-on projects that guide readers through real-world scenarios, such as deploying chatbots, image recognition systems, and more. These examples help bridge the gap between theory and practice, equipping readers with the skills needed to apply AI engineering principles effectively. -
question:
What skills will I learn by reading this book?
répondre: Readers will gain a solid understanding of foundational AI concepts, including model training, evaluation, and deployment. In addition, they will learn how to effectively use popular libraries like TensorFlow and PyTorch for implementing AI solutions. The book prepares readers to tackle complex challenges in AI engineering, enhancing their skill set for careers in technology and data science. -
question:
Is this book suitable for beginners in AI?
répondre: Yes, the book is structured to accommodate readers at various skill levels, including beginners. It starts with fundamental concepts and gradually introduces more advanced topics, ensuring that all readers can follow along. The clear explanations, combined with practical examples, make it accessible for those new to AI engineering while still offering valuable insights for experienced practitioners. -
question:
How can I apply the knowledge from this book in my career?
répondre: By applying the techniques and insights gained from this book, readers can enhance their ability to design and develop AI applications in their respective fields. Whether you're aiming for a role in AI research, software development, or data analysis, the skills taught in this book are highly relevant and transferable. Readers can showcase their knowledge by creating innovative projects and contributing to AI initiatives in their organizations. -
question:
What resources accompany this book?
répondre: The book may include supplementary resources such as online repositories, code examples, and access to a community of readers. These resources are designed to enhance the learning experience by providing additional materials that reinforce key concepts. Engaging with these resources allows readers to apply what they've learned and collaborate with others in the field, further enriching their understanding of AI engineering. -
question:
Where can I buy 'AI Engineering: Building Applications with Foundation Models 1st Edition' in Vanuatu?
répondre: You can buy 'AI Engineering: Building Applications with Foundation Models 1st Edition' on Ubuy, a reliable online marketplace that offers a wide selection of books and educational materials. Ubuy provides a user-friendly shopping experience and ensures that you can easily find this title along with related resources to enhance your understanding of AI engineering.
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Caractéristiques et avantages
- Learn the essentials of AI engineering and its distinction from traditional ML engineering.
- Discover a framework for developing AI applications from simple to advanced techniques.
- Explore model adaptation techniques like prompt engineering and fine-tuning.
- Understand the bottlenecks related to latency and cost in serving foundation models.
- Choose the right models, datasets, and evaluation metrics tailored to your needs.
- Written by industry expert Chip Huyen, offering insights into practical AI application development.
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Profitez d'une expérience d'achat sereine avec des produits 100 % originaux, une sécurité de paiement conforme PCI DSS, une protection des données certifiée ISO 27001, la livraison transfrontalière la plus rapide, les retours gratuits* et un emballage sécurisé pour chaque commande.