Difference between revisions of "Learning Techniques"
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* [https://machinelearningmastery.com/types-of-learning-in-machine-learning/ 14 Different Types of Learning in Machine Learning | Jason Brownlee - Machine Learning Mastery] | * [https://machinelearningmastery.com/types-of-learning-in-machine-learning/ 14 Different Types of Learning in Machine Learning | Jason Brownlee - Machine Learning Mastery] | ||
* * [[Large Language Model (LLM)]] ... [[Natural Language Processing (NLP)]] ...[[Natural Language Generation (NLG)|Generation]] ... [[Natural Language Classification (NLC)|Classification]] ... [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Understanding]] ... [[Language Translation|Translation]] ... [[Natural Language Tools & Services|Tools & Services]] | * * [[Large Language Model (LLM)]] ... [[Natural Language Processing (NLP)]] ...[[Natural Language Generation (NLG)|Generation]] ... [[Natural Language Classification (NLC)|Classification]] ... [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Understanding]] ... [[Language Translation|Translation]] ... [[Natural Language Tools & Services|Tools & Services]] | ||
| − | + | * [[Large Language Model (LLM)#Multimodal|Multimodal Machine Learning]] | |
<b>Core:</b> four main types of learning problems in machine learning | <b>Core:</b> four main types of learning problems in machine learning | ||
Revision as of 11:13, 29 April 2023
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- Artificial Intelligence (AI) ... Machine Learning (ML) ... Deep Learning ... Learning Techniques
- 14 Different Types of Learning in Machine Learning | Jason Brownlee - Machine Learning Mastery
- * Large Language Model (LLM) ... Natural Language Processing (NLP) ...Generation ... Classification ... Understanding ... Translation ... Tools & Services
- Multimodal Machine Learning
Core: four main types of learning problems in machine learning
- In-Context Learning (ICL) ... LLMs understand to encode learning algorithms implicitly during their training processes
- 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
- Ensemble Learning
- Multi-Task Learning (MTL)
- Apprenticeship Learning - Inverse Reinforcement Learning (IRL)
- Imitation Learning
- Simulated Environment Learning
- 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
