Difference between revisions of "Learning Techniques"
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* [[Multi-Task Learning (MTL)]] | * [[Multi-Task Learning (MTL)]] | ||
* [[Apprenticeship Learning - Inverse Reinforcement Learning (IRL)]] | * [[Apprenticeship Learning - Inverse Reinforcement Learning (IRL)]] | ||
| − | * [[Imitation Learning]] | + | * [[Imitation Learning (IL)]] |
* [[Lifelong Learning]] - Catastrophic Forgetting Challenge | * [[Lifelong Learning]] - Catastrophic Forgetting Challenge | ||
* [[Neural Structured Learning (NSL)]] | * [[Neural Structured Learning (NSL)]] | ||
Revision as of 07:54, 13 August 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- Artificial Intelligence (AI) ... Machine Learning (ML) ... Deep Learning ... Neural Network ... Reinforcement ... Learning Techniques
- 14 Different Types of Learning in Machine Learning | Jason Brownlee - Machine Learning Mastery
- Multimodal Machine Learning
Core: four main types of learning problems in machine learning
- In-Context Learning (ICL) ... Context ... Causation vs. Correlation ... Autocorrelation ... Out-of-Distribution (OOD) Generalization ... Transfer Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning (RL)
Hybrid: drawing from unsupervised and supervised learning
Other Techniques:
- Deep Learning
- Transfer Learning a model trained on one task is re-purposed on a second related task
- Few Shot Learning ... One-Shot Learning ... Zero-Shot Learning
- Ensemble Learning
- Multi-Task Learning (MTL)
- Apprenticeship Learning - Inverse Reinforcement Learning (IRL)
- Imitation Learning (IL)
- Lifelong Learning - Catastrophic Forgetting Challenge
- Neural Structured Learning (NSL)
- Meta-Learning
- Online Learning
- Human-in-the-Loop (HITL) Learning / Active Learning
- Decentralized: Federated & Distributed Learning
- Action Learning ... Embodied AI
- Simulated Environment Learning
