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所在平台: Udemy |
课程主页: https://www.udemy.com/course/foundations-of-ai-knowledge-representation-learning/
课程评论：没有评论
**课程名称：** 人工智能基础：知识表示与学习 **课程概述：** 本课程旨在帮助学习者理解计算机如何表示知识以及如何进行推理。课程将探讨多种图形化方法来表示知识，并深入研究机器学习的范式，重点关注如何获取、处理信息以及进行推理。学习者将了解机器学习的基本原理，以及能够推广知识的方法。课程还将区分学习型智能体与其它人工智能智能体的区别，并通过决策树和简单线性回归的实践来学习机器学习。 课程强调了智能在人类决策、招聘和问题解决中的核心作用，并追溯了人类理解智能演进的历史。知识的表示和推理是促进智能发展的关键要素。
In this course, we try to establish an understanding of how can computers or machines represent this knowledge and how can they perform inference. Representing information in the form of graphs, pictures and inferring information from pictures has been there since the inception of mankind. In this course, we look into few graphical methods of representing knowledge. In the second half of the course, we look into the learning paradigm. Learning or gaining information, processing information and reasoning are key concepts of Artificial Intelligence. In this course we look into the fundamentals of Machine Learning and methods that generalize knowledge. During this part of the journey, we will try to understand more about learning agent and how is it different from the other artificial intelligence agents. We will work on decision trees and simple linear regression as a part of machine learning in this course.Intelligence is a very complex element in Humans which drives our lives. Take a decision or hire a candidate or solve a problem, intelligence is the key contributor. Since the bronze age, we tried to understand the evolution of intelligence and what are the key aspects that promote intelligence. One key element in promoting intelligence is representing knowledge we have acquired and inferring from the existing knowledge or deduction.
