书籍 Heat Weekly Ranking

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.

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.

A must-read in the field of Artificial Intelligence, it will take you through the mysteries of Artificial Intelligence and trigger your infinite imagination of future technology.

This book profoundly explores the future direction of human civilization, predicts technological development, social change, and possible global challenges, and provokes readers to think endlessly about the fate of mankind and the future of the universe.

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.

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.

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.

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

An authoritative classic that systematically explains AI principles and techniques, with equal emphasis on theory and practice, and is a must-read for AI learners and researchers.

Explore the frontiers of AI innovation, lead a new era of intelligent creation, and transform the future of power work.

Understand how agent systems are organized through 21 design patterns, taking into account tool invocation, multi-agent collaboration, reliability, and evaluation.

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.

Highly recommended by OpenAI CEO Sam Altman!

In-depth analysis of how AI empowers thousands of industries

This book systematically introduces the basic principles, methods, and applications of deep learning and its recent advances in various fields, providing a comprehensive guide to understanding and building deep learning systems.