几本AIEngineeringBooks

sd010813

几本AIEngineeringBooks<br><br>https://linux.do/uploads/default/original/4X/8/4/b/84b4b3c96539e0d8d03134f9d4eb4bde33d45e81.jpeg<br>https://linux.do/uploads/default/optimized/4X/8/4/b/84b4b3c96539e0d8d03134f9d4eb4bde33d45e81_2_800x1000.jpeg<br>https://linux.do/uploads/default/optimized/4X/8/4/b/84b4b3c96539e0d8d03134f9d4eb4bde33d45e81_2_600x750.jpeg<br>https://linux.do/uploads/default/optimized/4X/8/4/b/84b4b3c96539e0d8d03134f9d4eb4bde33d45e81_2_400x500.jpeg<br><br>链接: 百度网盘 提取码: hj7m AI Engineering: Building Applications with Foundation Models by Chip Huyen: This book is frequently cited as a foundational text, covering the process of building applications using readily available foundation models and how it differs from traditional ML engineering. Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications by Chip Huyen: Often considered complementary to the above, this book focuses on designing scalable, reliable, and maintainable ML systems, from data handling to deployment and monitoring. LLM Engineer’s Handbook: Master the Art of Engineering Large Language Models from Concept to Production by Paul Iusztin &amp; Maxime Labonne: This book offers practical guidance and “recipes” for moving Large Language Model (LLM) projects from prototype to production. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron: Praised for its practical approach, this guide covers core ML and deep learning concepts with real-world examples and popular Python libraries. Build a Large Language Model (From Scratch) by Sebastian Raschka: This book is recommended for gaining a deep, fundamental understanding of how LLMs work internally by building one from the ground up. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Often referred to as the “bible” of modern AI foundations, this provides a comprehensive mathematical and conceptual background for deep learning. Prompt Engineering for LLMs by John Berryman &amp; Albert Ziegler: These titles cover techniques for optimizing prompts and model outputs, a critical skill in modern AI development. The AI Engineering Bible by Thomas D. Caldwell: Positioned as a comprehensive reference for contemporary AI engineering practices. Designing Data-Intensive Applications by Martin Kleppmann: Though not exclusively an AI book, it is highly recommended for building scalable and reliable data systems, which is crucial infrastructure for production AI. 3<br><br>更多资料请搜索AI综合资料分享中心（智能体）：http://youhuasdyy.cn/<br><br>更多资料请搜索AI综合资料分享中心（智能体）：http://youhuasdyy.cn/<br><br>================================<br>(每日分享）教育资源合集（幼儿）https://pan.quark.cn/s/7874ce6eda4c<br>(每日分享）教育资源合集（小学）https://pan.quark.cn/s/cef036d70c9a<br>(每日分享）教育资源合集（初中）https://pan.quark.cn/s/f23f43019b3e<br>(每日分享）教育资源合集（高中）https://pan.quark.cn/s/5be5155408c4<br>(每日分享)设计素材模板合集 https://pan.quark.cn/s/9bb2183818f4<br>(每日分享）小说合集 https://pan.quark.cn/s/e5ffebf2dc08<br>(每日分享）漫画合集 https://pan.quark.cn/s/c1bf77274f74<br>(每日分享)有声读物合集 https://pan.quark.cn/s/0cce76b31516<br>(每日分享）生活娱乐日常常识资料 https://pan.quark.cn/s/2d5b1971d8f2<br>(每日分享)手机软件合集 https://pan.quark.cn/s/dbbd31d627d4<br>(每日分享)电脑软件合集 https://pan.quark.cn/s/b0d2e85857d3<br>(每日分享)AI类教程合集资料https://pan.quark.cn/s/a2d9c8c60783<br>(每日分享)计算机编程类教程合集https://pan.quark.cn/s/bb4fc071ed06<br>(每日分享)自媒体教程合集资料https://pan.quark.cn/s/2ec0f7c89ba5<br>(每日分享)游戏资源合集（手机）https://pan.quark.cn/s/9db7b6beb378<br>(每日分享)游戏资源合集（电脑）https://pan.quark.cn/s/7d15e104b776<br>(每日分享)网赚项目资源合集https://pan.quark.cn/s/df566ff277ae<br>百度网盘网赚教程合集（提取码：pdbk）https://pan.baidu.com/s/1OTzE10CxVN18tkCZbzhbDw?pwd=pdbk<br>(每日分享）图片壁纸 https://pan.quark.cn/s/defba653fce8<br>(每日分享）音乐MV资源合集 https://pan.quark.cn/s/e050ee714063<br>(每日分享)考公合集 https://pan.quark.cn/s/383e4e5191f1<br>(每日分享）B站充电VIP视频合集 https://pan.quark.cn/s/88bc1f42b7e8

苍风以岚

楼主辛苦了

四风巧风

支持一下

无妄帅红

无回帖，不论坛，这才是人道。

明杰小仙女

Thomas Carmen

顶起