The Chinese name of this lesson is "机器学习的动机与应用". The English name may be "Motivation and Application of Machine Learning", I think.

This lesson introduces an overview of machine learning. The teacher, Andrew Ng, said that machine learning was such a technology which can be applied to many areas. He was very excited to teach this lesson.

The concept "Machine Learning" refers to the technogy that gives the computer to learn without being explictly programmed. Its learning ability learns from the experience and improves the performance by itself.

There are two aspects in Machine Learning, namely supervised learning and unsupervised learning. For supervised learning, you give computer the right answers and computer will from them. Regression and classification are both of supervised learning. For regression, the answer is continuous values. And for classification, the answer is discrete values. And for unsupervised learning, there are no answers to be told to the computer. It is mainly used to understand the structure of data. Clustering is of unsupervised learning.

Lastly, reinforcement learning was also being introduced. Reinforcement learning is used in the scenario that computer needs to make a sequence of decisions. After every decision, a reward or a punishment will be given. The decision made by reinforcement learning is to maximize the rewards and minimize the punishments. It‘s really like training a dog. When the dog do bad things, you say "bad dog" and shout at the dog. When the dog do good things, you say "good dog" and pat its head. Then by and by, the dog will know how to do to maximize "good dogs" and minimize "bad dogs".

standford cs229 lesson1