DeepSeek in Action
eBook - ePub

DeepSeek in Action

LLM Deployment, Fine-Tuning, and Application

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

DeepSeek in Action

LLM Deployment, Fine-Tuning, and Application

About this book

From fundamental concepts to advanced implementations, this book thoroughly explores the DeepSeek-V3 model, focusing on its Transformer-based architecture, technological innovations, and applications.

The book begins with a thorough examination of theoretical foundations, including self-attention, positional encoding, the Mixture of Experts mechanism, and distributed training strategies. It then explores DeepSeek-V3's technical advancements, including sparse attention mechanisms, FP8 mixed-precision training, and hierarchical load balancing, which optimize memory and energy efficiency. Through case studies and API integration techniques, the model's high-performance capabilities in text generation, mathematical reasoning, and code completion are examined. The book highlights DeepSeek's open platform and covers secure API authentication, concurrency strategies, and real-time data processing for scalable AI applications. Additionally, the book addresses industry applications, such as chat client development, utilizing DeepSeek's context caching and callback functions for automation and predictive maintenance.

This book is aimed primarily at AI researchers and developers working on large-scale AI models. It is an invaluable resource for professionals seeking to understand the theoretical underpinnings and practical implementation of advanced AI systems, particularly those interested in efficient, scalable applications.

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Yes, you can access DeepSeek in Action by Jing Dai in PDF and/or ePUB format, as well as other popular books in Computer Science & Natural Language Processing. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. Preface
  7. Part I Theoretical Foundations and Technical Architecture of Generative AI
  8. Part II Development and Application of Generative AI and Advanced Prompt Design
  9. Part III Integration of Practical Experience and Advanced Applications
  10. Postscript
  11. References