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本书是一部讲解清晰、图解丰富的大语言模型技术指南，深度剖析核心原理与实战技巧，为大语言模型项目研发、面试或出于好奇心了解大语言模型核心原理的同学提供强大助力。

全书共分为五个部分：

基础篇：以精炼严谨的内容帮助你迅速掌握神经网络基础与深度学习中的关键概念，为后续学习打下坚实理论基础
嵌入篇：深入探讨分词算法、词嵌入（如 word2vec）以及句子嵌入（如 RNN、LSTM、GRU）
Transformer篇：详解自注意力机制背后的原理，全面解析编码器-解码器架构及其相关变种，如 BERT、GPT 和 T5，并附有加速计算的技巧与窍门
大语言模型篇：探究基于 Transformer 模型的调优策略，包括提示工程、参数高效微调和偏好调整
应用篇：聚焦情感抽取、机器翻译、检索增强生成等热门应用场景

此外，本页面提供自主领取 15% 的折扣优惠，旨在回馈已购买纸质版的读者，并兼顾各国家和地区的购买力平价。非常感谢您的关注与支持！

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