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6.867机械学习(麻省理工学院)

6.867 Machine Learning (MIT)
课程网址: http://ocw.mit.edu/courses/electrical-engineering-and-computer-sc...  
主讲教师: Rohit Singh; Prof. Tommi Jaakkola; Ali Mohammad
开课单位: 麻省理工学院
开课时间: 2006-07-15
课程语种: 英语
中文简介:
6.867是一个关于机器学习的入门课程,概述了机器学习中的许多概念,技术和算法,从分类和线性回归等主题开始,最后介绍了最新的主题,如增强,支持向量机,隐马尔可夫模型和贝叶斯网络。该课程将为学生提供现代机器学习方法背后的基本思想和直觉,以及对其工作方式,原因和时间的更正式理解。课程的基本主题是统计推断,因为它为所涵盖的大多数方法提供了基础。
课程简介: 6.867 is an introductory course on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. The course will give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work. The underlying theme in the course is statistical inference as it provides the foundation for most of the methods covered.
关 键 词: 机器学习; 线性回归; 后现代的机器学习方法
课程来源: 麻省理工公开网
入库时间: 2013-10-14
最后编审: 2020-05-30:王勇彬(课程编辑志愿者)
阅读次数: 561