监督学习的两个分类：回归和分类
Unsupervised learning AIM:
-create an internal representation of the input that is useful for subsequent supervised or reinforcement learning
-It provides a compact ,low-dimensional reqresentation of the input.高维数据往往存在或者近似于一个低维流形（low-dimensional manifold）(PCA)
-It provides an economical high-dimensional representation of the input in terms of learned features.
-Binary features are economical(每个变量只需要一个比特来说明其状态)
-So are real-valued features that are nearly all zero.
-It finds sensible clusters in the input.聚类是非常稀疏的编码，对于每个聚类我们有一个变量。