# 机器学习基础 – 数学基础

## Machine Learning Foundations-Mathematical Foundations

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Coursera
• 完成时间大约为 16 个小时
• 简单（初级）
• 中文

### 课程概况

Machine learning is an exciting field with lots of applications in engineering, science, finance, and commerce. It is also a very dynamic field, where many new techniques are being designed every day, and the hot techniques and theories at times can rise and disappear rapidly. Thus, users of machine learning from other fields often face the problem of choosing or using the techniques properly. In this course, we emphasize the necessary fundamentals that give any student of machine learning a solid foundation, and enable him or her to exploit current techniques properly, explore further techniques and theories, or perhaps to contribute their own in the future.

### 课程大纲

what machine learning is and its connection to applications and other fields
5 个视频 （总计 70 分钟）, 5 个阅读材料

your first learning algorithm (and the world's first!) that "draws the line" between yes and no by adaptively searching for a good line based on data
4 个视频 （总计 61 分钟）

learning comes with many possibilities in different applications, with our focus being binary classification or regression from a batch of supervised data with concrete features
4 个视频 （总计 61 分钟）

learning can be "probably approximately correct" when given enough statistical data and finite number of hypotheses
4 个视频 （总计 60 分钟）, 1 个测验

what we pay in choosing hypotheses during training: the growth function for representing effective number of choices
4 个视频 （总计 53 分钟）

test error can approximate training error if there is enough data and growth function does not grow too fast
4 个视频 （总计 52 分钟）

learning happens if there is finite model complexity (called VC dimension), enough data, and low training error
4 个视频 （总计 50 分钟）

learning can still happen within a noisy environment and different error measures

### 参考资料

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