相關主題
商品描述
This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated third edition also includes new material on deep learning.
Topics and features:
- Presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website
- Introduces convolutional neural networks as the currently most important type of deep learning networks with applications to image classification (NEW)
- Contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons
- Reports on developments in deep learning, including applications of neural networks to large language models as used in state-of-the-art chatbots as well as to the generation of music and art (NEW)
- Includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks, and reinforcement learning
- Covers various classical machine learning algorithms and introduces important general concepts such as cross validation, data normalization, performance metrics and data augmentation (NEW)
- Includes a section on AI and society, discussing the implications of AI on topics such as employment and transportationIdeal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material.
Dr. Wolfgang Ertel is a professor at the Institute for Artificial Intelligence at the Ravensburg-Weingarten University of Applied Sciences, Germany.
商品描述(中文翻譯)
這本易於理解且引人入勝的教科書對人工智慧（AI）這一令人興奮的領域提供了簡明的介紹。廣泛的討論涵蓋了該領域內的主要子學科，描述了在代理、邏輯、搜尋、不確定性推理、機器學習、神經網絡和強化學習等領域中的實用算法和具體應用。這本備受期待的第三版經過全面修訂和更新，還包括有關深度學習的新材料。
主題與特色：
- 提供以應用為重點的實作學習方法，並在相關網站上提供補充教學資源。
- 介紹卷積神經網絡，作為當前最重要的深度學習網絡類型，應用於圖像分類（新）。
- 包含大量的學習練習和解答、突出的例子、定義、定理和插圖漫畫。
- 報告深度學習的發展，包括神經網絡在大型語言模型中的應用，這些模型用於最先進的聊天機器人，以及音樂和藝術的生成（新）。
- 包括有關謂詞邏輯、PROLOG、啟發式搜尋、概率推理、機器學習和資料挖掘、神經網絡和強化學習的章節。
- 涵蓋各種經典的機器學習算法，並介紹重要的一般概念，如交叉驗證、資料正規化、性能指標和資料增強（新）。
- 包含有關AI與社會的部分，討論AI對就業和交通等主題的影響。
這本易讀的教科書非常適合人工智慧的基礎課程或模組，為計算機科學及其他技術學科的學生提供了該領域的優秀概述，理解這些材料只需具備高中數學水平的知識。
德國拉芬斯堡-瓦因根應用科技大學人工智慧研究所的教授 Wolfgang Ertel 博士。
作者簡介
作者簡介(中文翻譯)
德國拉芬斯堡-維根塔大學應用科學院人工智慧研究所的教授 Wolfgang Ertel 博士。
