书籍 Heat Monthly 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.

Highly recommended by OpenAI CEO Sam Altman!

A technical reference book on Chinese large language models, written by a research team at Renmin University of China, is intended for readers with a foundation in deep learning who wish to establish a systematic technical framework.

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.

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

Focusing on models, strategies, and algorithms, this book provides a systematic introduction to supervised, unsupervised, deep, and reinforcement learning. It is ideal for technical readers who are committed to strengthening their mathematical foundations.

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.

Zhou Zhihua’s introductory textbook on machine learning—covering topics from model evaluation to classic algorithms—is ideal for learners who want to solidify their theoretical foundation and understand the logic behind model selection.

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.

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.

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.

This course bridges the gap between understanding AI technology and gaining insights into user needs, model evaluation, and product design. It is ideal for product managers and cross-functional teams responsible for implementing AI solutions.

This course connects calculus, linear algebra, and probability and statistics to AI problems, making it ideal for strengthening your mathematical foundation while learning algorithms and testing your understanding through Python exercises.

In-depth analysis of how AI empowers thousands of industries