## Learning From Data

 所在平台: EdxArchive 课程类别: 计算机科学 大学或机构: caltechx 授课老师： Yaser S. Abu-Mostafa

#### 课程详情

This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to automatically learn how to perform a desired task based on information extracted from the data. ML has become one of the hottest fields of study today, taken up by undergraduate and graduate students from 15 different majors at Caltech. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects. The lectures follow each other in a story-like fashion:

• What is learning?
• Can a machine learn?
• How to do it?
• How to do it well?
• Take-home lessons.

The topics in the story line are covered by 18 lectures of about 60 minutes each plus Q&A.

• Lecture 1: The Learning Problem
• Lecture 2: Is Learning Feasible?
• Lecture 3: The Linear Model I
• Lecture 4: Error and Noise
• Lecture 5: Training versus Testing
• Lecture 6: Theory of Generalization
• Lecture 7: The VC Dimension
• Lecture 9: The Linear Model II
• Lecture 10: Neural Networks
• Lecture 11: Overfitting
• Lecture 12: Regularization
• Lecture 13: Validation
• Lecture 14: Support Vector Machines
• Lecture 15: Kernel Methods
• Lecture 16: Radial Basis Functions
• Lecture 17: Three Learning Principles
• Lecture 18: Epilogue

#### 课程评论(1条)

 0 EyonFresh 2013-10-01 12:57 0 票支持; 0 票反对 刚开始看第一节课，先留个脚印吧~据说这门课会比较偏理论一些，在NG那门机器学习开始入门之后，我希望这门课能够带我进入ML的更深一个层次的level。当然不是说这两门课的差距，而是希望自己更加用心一些。有兴趣的可以一起加301886009这个qq群一起探讨噢。【p,s:这门课的教学视频直接就是Yaser在加州理工上课时候的视频，另外还有很多在线辅助教学的工具，我也还在探索中。】

#### 课程简介

Introductory Machine Learning course covering theory, algorithms and applications. Our focus is on real understanding, not just "knowing."