Difference between revisions of "Machine Learning"
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Machine Learning is | {{WikiEntry|key=Machine Learning|qCode=2539}} is the scientific study of algorithms and statistical models that computer systems use to perform tasks without explicit instructions. | ||
[https://www.turing.org.uk/scrapbook/test.html The Alan Turing Internet Scrapbook] | [https://www.turing.org.uk/scrapbook/test.html The Alan Turing Internet Scrapbook] | ||
Revision as of 10:50, 19 March 2022
| Machine Learning | |
|---|---|
| Term | Machine Learning |
| Knowledge Domain | Computing Science, Artificial Intelligence |
| Parent Domain | Cognitive Science |
Machine Learning(Q2539) is the scientific study of algorithms and statistical models that computer systems use to perform tasks without explicit instructions.
The Alan Turing Internet Scrapbook
All computation or decision-making processes can be considered as a scientific approximation of real-world events in spacetime. The notion of Abstract Interpretation (AI), also known as a field of to efficiently approximate decision/computational procedures. Clearly, this is different from Artificial Intelligence, also abbreviate as AI.
{{#ev:youtube|https://www.youtube.com/watch?v=wGswp5A0jkQ%7C%7C%7C%7C%7C}}
As Prof. Lazarus has presented, there is 3 main kinds of algorithms typically used to accomplished machine learning, which you might use to process your data; depending on which phase your are in or what you hope to accomplish you might end up using all these options:
- Supervised learning
- Regression
- Classification
- Unsupervised learning
- Clustering
- Anomaly Detection
- Compression
- Reinforcement learning
- Model Free
- Model Based
- Transfer Learning
Important Publications
One of the key idea in machine learning came from the PAC assumption by Leslie Valiant. His ideas can be found in this book[1].
References
- ↑ Valiant, Leslie (2013). Probably Approximately Correct - Nature’s Algorithms for Learning and Prospering in a Complex World. local page: Basic Books. ISBN 978-0-465-03271-6.