Machine learning
-Grew out of work in AI
-New capability for computers
Examples:
-Database mining
medical records,computational biology,engineering
-Applications can't program by hand
handwriting recognition, most of Natural Language Processing(NLP), Computer
Vision
-Self-customizing programs
-Understanding human learning(brain, real AI)
Machine Learning definition:
Tom Michell(1988) Well-posed Learning Problem: A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.
T: Classifying emails as spam or not spam
E: Watching you label emails as spam or not spam
P(性能度量): The number(or fraction) of emails correctly classified as spam/not spam
The main two types are what we call supervised learning and unsupervised
Machine Learning algorithms:
- supervised learning
- unsupervised learning
Others: Reinforcement learning, recommender systems.
Also talk about: Practical advice for applying learning algorithms.
