3. Types-of-learning

发表于 2019-03-31 | 分类于 machine learning foundation

When can machines learn? (illustrative + technical)

Learning with different output space Y

Classification, Multiclass Classification
Regression
Structured Learning

Learning with different data label y_n

Supervised
Unsupervised
Other Unsupervised Learning Problems: clustering/density estimation/outlier detection
Semi-supervised
Reinforcement Learning

learning with different protocal f(x_n,y_n)

learning with different input space X

concrete: sophisticated (and related) physical meaning
raw: simple physical meaning
abstract: no (or little) physical meaning

Why can machines learn? (theoretical +illustrative)

How can machines learn? (technical +practical)

How can machines learn better? (practical + theoretical)