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Machine Learning

Machine Learning (.pdf)

Definitions

• ‘Machine learning is a science of the artificial. The field's main objects of study are artifacts, specifically algorithms that improve their performance with experience.’
  Langley, 1996
• ‘Machine Learning is the study of computer algorithms that improve automatically through experience.’
  Mitchell, 1997
• ‘Machine learning is programming computers to optimize a performance criterion using example data or past experience.’
  Alpaydin, 2004
• ‘Machine learning is an area of artificial intelligence concerned with the development of techniques which allow computers to “learn”.’
  Wikipedia, 2005
• ‘A field of AI concerned with programs that learn. It includes Reinforcement Learning and Neural Networks among many other fields.’
  Artificial Intelligence FAQ, 2004
• Machine learning is an area of artificial intelligence concerned with the study of computer algorithms that improve automatically through experience. In practice, this involves creating programs that optimize a performance criterion through the analysis of data.
  Sewell, 2006

Due to the no free lunch theorems, machine learning within academia often consists of searching for data sets that show a novel algorithm in a favourable light.

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Pattern Recognition

Feature Selection

Model Selection

Ensemble Learning

Artificial Neural Networks

Support Vector Machines

Books

• ALPAYDIN, Ethem, 2004. Introduction to Machine Learning. Cambridge, MA: The MIT Press.
• BISHOP, Christopher M., 2006. Pattern Recognition and Machine Learning. Information Science and Statistics. New York: Springer.
• LANGLEY, Pat, 1996. Elements of Machine Learning. San Francisco, CA: Morgan Kaufmann.
• MITCHELL, Tom M., 1997. Machine Learning. New York: McGraw-Hill.

Links

• Wikipedia: Category:Machine learning
• Wikipedia: Machine learning
• Google Directory
• Machine Learning Resources by David W. Aha
• Artificial Neural Networks (ANNs)
• Support Vector Machines (SVMs)
• Machine Learning and Statistics
• Machine Learning (Theory) » All Models of Learning have Flaws

Bibliography

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