Difference between revisions of "Learning Techniques"
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− | <b>Learning Techniques:</b> | + | <b>Other types of Learning Techniques:</b> |
* [[Active Learning]] | * [[Active Learning]] | ||
* [[Online Learning]] | * [[Online Learning]] |
Revision as of 13:11, 8 December 2019
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- 14 Different Types of Learning in Machine Learning | Jason Brownlee - Machine Learning Mastery
- Natural Language
Learning Problems: three main types of learning problems in machine learning
Hybrid Learning Problems: The lines between unsupervised and supervised learning is blurry, and there are many hybrid approaches that draw from each field of study.
Statistical Inference: Inference refers to reaching an outcome or decision. In machine learning, fitting a model and making a prediction are both types of inference. There are different paradigms for inference that may be used as a framework for understanding how some machine learning algorithms work or how some learning problems may be approached.
- Inductive Learning
- Deductive Inference
- Transductive Learning
Other types of Learning Techniques:
- Active Learning
- Online Learning
- Text Transfer Learning
- Image/Video Transfer Learning
- Few Shot Learning
- Transfer Learning a model trained on one task is re-purposed on a second related task
- Ensemble Learning
- Multi-Task Learning (MTL)
- Apprenticeship Learning - Inverse Reinforcement Learning (IRL)
- Imitation Learning
- Simulated Environment Learning
- Lifelong Learning - Catastrophic Forgetting Challenge