Difference between revisions of "Machine Learning"
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# [[Supervised learning]] | # [[Supervised learning]] | ||
## Regression | |||
## Classification | |||
# [[Unsupervised learning]] | # [[Unsupervised learning]] | ||
## Clustering | |||
## Anomaly Detection | |||
## Compression | |||
# [[Reinforcement learning]] | # [[Reinforcement learning]] | ||
## Model Free | |||
## Model Based | |||
## Transfer Learning | |||
[[Category:Technical Term]] | [[Category:Technical Term]] |
Revision as of 06:16, 6 June 2021
Machine Learning | |
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Term | Machine Learning |
Knowledge Domain | Computing Science, Artificial Intelligence |
Parent Domain | Cognitive Science |
Machine Learning is a field derived from Computing Science.
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