Agentic Design Patterns
Understand how agent systems are organized through 21 design patterns, taking into account tool invocation, multi-agent collaboration, reliability, and evaluation.
Kouzi Develops AI Agent Applications
Learn how to develop AI agent applications through hands-on projects focused on the Kouzhi platform’s workflows, knowledge base, prompts, and database.
12 Lectures on AI: An Introduction to Artificial Intelligence
Covering everything from the principles of large language models to creative applications and educational issues, this book is ideal for general readers, teachers, and parents who wish to build a foundation of knowledge about AI.
The Wave Is Coming: Technology, Power, and the Clash of the Future
Starting with the diffusion of AI and biotechnology, this book explores technological capabilities, power structures, and governance challenges; it is suitable for Chinese-speaking readers who wish to move beyond a purely tool-oriented perspective.
Data Analysis with AI—Using DeepSeek, Doubao, and Zhipu Qingyan to Boost Efficiency by a Factor of N
Integrate tools such as DeepSeek into your daily analysis workflow, focusing on prompt creation, data analysis tasks, and result validation; ideal for operations, business, and data professionals who want to learn by doing.
Large-Scale Language Models: From Theory to Practice (2nd Edition)
This book integrates data, training, fine-tuning, reinforcement learning, agents, RAG, efficiency optimization, and evaluation of large language models within a Chinese-language framework, making it suitable for technically advanced readers with a background in programming.
The Underlying Logic of Artificial Intelligence
From search, perception, and learning to reasoning, this book establishes a knowledge framework for understanding artificial intelligence from a general education perspective, making it ideal for Chinese readers who wish to grasp the technical principles and limitations of the technology.
AI Agents in Action (2nd Edition · Original English Edition)
Focusing on tool invocation, MCP, knowledge and memory, evaluation, and multi-agent collaboration, this course teaches you how to turn Python prototypes into verifiable agent applications. It is suitable for practitioners with a background in programming.
Designing Machine Learning Systems (Original English Edition)
From data, evaluation, and deployment to continuous monitoring, gain an understanding of the engineering trade-offs involved in implementing machine learning systems. Ideal for engineers and technical leads who want to turn offline models into long-term, maintainable services.
Deep Learning with Python (3rd Edition · Original English Edition)
Move from the fundamentals of deep learning to image, text, and generative AI, and build practical skills using Keras 3 and mainstream frameworks. Suitable for readers with a basic understanding of Python who want to systematically expand their knowledge of machine learning models.
Building a Large Model from Scratch
A step-by-step guide to implementing a GPT-style language model using PyTorch, covering text processing, attention mechanisms, pretraining, and fine-tuning. Suitable for developers with a basic understanding of Python who want to understand the underlying implementation of large language models.
Prompt Engineering for Large Models: The Science and Art of Building Large Model Applications
Focusing on prompt design, context organization, RAG, and agent workflows, learn how to build evaluable, iterable large-model applications. Suitable for AI application developers and technical product managers with a background in programming.
The Era of Collective Intelligence: How to Coexist with AI
Drawing on the perspectives of work, learning, and creativity, this book explains how to collaborate with AI, verify results, and maintain human judgment. It is ideal for readers who want to incorporate AI into their daily work without blindly relying on it.
AI Engineering: Hands-On Development of Large-Scale Model Applications
This course examines the engineering challenges involved in taking an AI application from prototype to deployment, focusing on model selection, quality assessment, RAG, fine-tuning, and cost optimization. It is designed for developers, technical leads, and technical product managers who wish to establish a systematic approach.
Illustrated Guide to Large Models: Principles and Practical Applications of Generative AI
Use diagrams to understand word embeddings, embeddings, and Transformers, then move on to practical applications of semantic search, RAG, and fine-tuning. Suitable for readers with some Python background who want to connect the concepts of large language models into a cohesive system.
Homo sapiens on top of that
Phenomenal bestseller "A Brief History of Humankind" Yuval Hraley precipitated six years of masterpiece; information network determines cognition, cognition determines how far you can go
The AI Revolution - How Artificial Intelligence can empower business
How AI is rewriting the future of humanity and the world of business. This book tells many amazing stories about ordinary people building differentiated approaches to AI.
Enterprise AI Journey
In-depth analysis of how AI empowers thousands of industries