Artificial Intelligence: Chapter 5 -
Machine Learning
Definition:
A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.
Why is Machine Learning Important?
Some tasks cannot be defined well, except by examples (e.g., recognizing people). Relationships and correlations can be hidden within large amounts of data. Machine Learning/Data Mining may be able to find these relationships. Human designers often produce machines that do not work as well as desired in the environments in which they are used.
The amount of knowledge available about certain tasks might be too large for explicit encoding by humans (e.g., medical diagnostic). Environments change over time. New knowledge about tasks is constantly being discovered by humans. It may be difficult to continuously re-design systems “by hand”.
Why “Learn”?
Machine learning is programming computers to optimize a performance criterion using example data or past experience. There is no need to “learn” to calculate payroll
Learning is used when:
- Human expertise does not exist (navigating on Mars),
- Humans are unable to explain their expertise (speech recognition)
- Solution changes in time (routing on a computer network)
- Solution needs to be adapted to particular cases (user biometrics)
Machine learning is primarily concerned with the accuracy and effectiveness of the computer system.
Download Direct Link: https://www.scribd.com/doc/309734588/Artificial-Intelligence-Chapter-5-Machine-Learning
No comments:
Post a Comment