定 价:59.8 元
丛书名:
- 作者:朱琼瑶
- 出版时间:2026/2/1
- ISBN:9787121522147
- 出 版 社:电子工业出版社
适用读者:本教材可以作为各类职业院校、应用型本科人工智能通识课的教材,也适合对人工智能感兴趣或有相关需求的社会人士阅读。
- 中图法分类:TP18
- 页码:238
- 纸张:
- 版次:01
- 开本:16开
- 字数:380.799987792969(单位:千字)
本教材以项目任务驱动和活页式设计为核心,紧密围绕人工智能技术前沿,系统涵盖自然语言处理、语音与图像识别、机器学习、AIGC生成技术、具身智能及伦理治理等关键领域。项目内容跨专业应用融合,结合智能制造、医疗、金融等企业真实场景案例,依托定制化实验平台与低代码工具,配套微课、实操手册等数字化资源,支持理论与实践深度融合。教材通过"问题引导—探索实践—知识构建”流程,培养学生自主探究与解决多领域实际问题的能力,并融入人工智能伦理与社会责任思考,赋能高职学生成为智能时代所需的复合型技术技能人才。
朱琼瑶,女,现任安康职业技术学院教师,长期从事计算机专业教学工作及管理工作,主要研究方向为人工智能与计算机。曾发表多篇学术论文,参与多项课题研究并取得相应成果。
第1部分 认识人工智能 ··················································································.1
项目1 让机器“学会”学习——深度学习与智能引擎 ······························································.3
任务1 寻找身边的智能应用 ·························································································.3
任务2 回归模型 ········································································································.5
任务3 分类模型 ········································································································11
任务4 聚类分析 ······································································································.19
任务5 交互式可视化人工神经网络 ··············································································.24
项目2 让机器“理解”文字——自然语言处理 ·····································································.30
任务1 短文本相似度分析 ··························································································.30
任务2 新闻文本分类 ································································································.35
任务3 新闻评论情感分析 ··························································································.40
项目3 让机器“听懂”声音——语音识别与合成 ··································································.45
任务1 语音信号处理 ································································································.45
任务2 文本生成语音 ································································································.51
任务3 实时语音翻译 ································································································.56
项目4 让机器“看清”世界——计算机视觉 ········································································.61
任务1 目标检测 ······································································································.61
任务2 图像分类 ······································································································.67
任务3 图像识别 ······································································································.77
项目5 让机器“创作”内容——大语言模型与AIGC ·····························································.85
任务1 提示词工程 ···································································································.85
任务2 AI 图像生成 ··································································································.91
任务3 AI视频理解 ··································································································.96
任务4 AI视频生成 ·································································································.100
第2部分 人工智能应用 ···············································································.107
项目6 AI+智能办公 ·····································································································.109
任务1 基于大模型快速生成思维导图 ··········································································.109
任务2 办公自动化与 PPT 自动生成 ·············································································.117
任务3 办公自动化与 Excel 表格处理 ···········································································.125
任务4 办公自动化与 Excel 图表分析 ···········································································.135
项目7 AI+教育人文 ·····································································································.145
任务1 图文创作 ·····································································································.145
任务2 试卷批改 ·····································································································.154
任务3 构建成语填空练习助手 ···················································································.159
任务4 创建教学教案生成器 ······················································································.167
项目8 AI+医疗健康 ·····································································································.178
任务1 基于机器学习的心脏病预测 ·············································································.178
任务2 基于深度学习的癌细胞与正常细胞的自动鉴别 ·····················································.188
任务3 构建医疗领域的知识图谱 ················································································.196
任务4 基于本地知识库的中医药知识问答助手 ······························································.201
第3部分 项目实践 ·····················································································.213
项目9 中华美食制作助手 ······························································································.215
任务1 初始化智能体与角色设定 ················································································.216
任务2 打造智能体的核心能力——搭建菜谱生成工作流 ··················································.219
任务3 集成图片生成与海报制作 ················································································.227
任务4 整体测试与发布分享——优化体验并交付成果 ·····················································.234