DeepSeek in Practice: From basics to fine-tuning, distillation, agent design, and prompt engineering of open source LLM

Andy Peng, Alex Strick van Linschoten, Duarte O.Carmo

Gain hands-on experience building, fine-tuning, and deploying GenAI applications using DeepSeek

Key Features

Explore DeepSeek’s architecture, training data, and reasoning capabilities

Build agents, fine-tune with distillation, and deploy with CI/CD pipelines

Apply DeepSeek to real-world use cases like coding, ideation, and legal analysis

Book Description

Learn how to build, fine-tune, and deploy AI systems using DeepSeek, one of the most influential open-source large language models available today. This book guides you through real-world DeepSeek applications—from understanding its core architecture and training foundations to developing reasoning agents and deploying production-ready systems.

Starting with a concise synthesis of DeepSeek’s research, breakthroughs, and open-source philosophy, you’ll progress to hands-on projects including prompt engineering, workflow design, and rationale distillation. Through detailed case studies—ranging from document understanding to legal clause analysis—you’ll see how to use DeepSeek in high-value GenAI scenarios.

You’ll also learn to build sophisticated agent workflows and prepare data for fine-tuning. By the end of the book, you’ll have the skills to integrate DeepSeek into local deployments, cloud CI/CD pipelines, and custom LLMOps environments.

Written by experts with deep knowledge of open-source LLMs and deployment ecosystems, this book is your comprehensive guide to DeepSeek’s capabilities and implementation.

What you will learn

Discover DeepSeek’s unique traits in the LLM landscape

Compare DeepSeek’s multimodal features with leading models

Consume DeepSeek via the official API, Ollama, and llama.cpp

Use DeepSeek for coding, document understanding, and creative ideation

Integrate DeepSeek with third-party platforms like OpenRouter and Cloudflare

Distill and deploy DeepSeek models into production environments