Kim Dong-sik: Basic Mathematics for Artificial Intelligence Explained in an Easy-to-Understand Way

As artificial intelligence rapidly evolves as a core technology of the Fourth Industrial Revolution, our lives are becoming more convenient and abundant. AI is used in virtual assistants, self-driving cars, medical diagnosis, and many other fields. Generative AI models such as ChatGPT have shown the public how dramatically the technology is advancing. AI applications are expanding throughout industry, the economy, culture, the arts, and society at large, leading experts to say the age of AI is about to begin. Students encountering AI products in daily life may wonder how AI can perceive, think, and use language like a person. Yet students interested in AI can be discouraged by the amount of mathematics in related books and conclude that learning AI is difficult. Mathematics matters because every stage, from data input to output and from building a model to running its learning algorithm, is expressed mathematically. Vectors and matrices from linear algebra represent data and models; optimization techniques involving derivatives and partial derivatives train AI models. Probability is used to make predictions, and understanding data trends requires concepts such as linear regression and gradient descent.

Korean title: 알기 쉽게 풀어쓴 인공지능 기초수학

Korean author: 김동식

Korean publisher: 생능출판

ISBN-13: 9791192932699