Explainable AI: Foundations, Methodologies and Applications
Mayuri Mehta · Vasile Palade · Indranath Chatterjee
2022年10月 · Intelligent Systems Reference Library 第 232 本图书 · Springer Nature
电子书
256
页
report评分和评价未经验证 了解详情
关于此电子书
This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.
The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.
为此电子书评分
欢迎向我们提供反馈意见。
如何阅读
智能手机和平板电脑
笔记本电脑和台式机
您可以使用计算机的网络浏览器聆听您在 Google Play 购买的有声读物。
电子阅读器和其他设备
如果要在 Kobo 电子阅读器等电子墨水屏设备上阅读，您需要下载一个文件，并将其传输到相应设备上。若要将文件传输到受支持的电子阅读器上，请按帮助中心内的详细说明操作。
