Difference between revisions of "Machine Learning (ML)"

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[https://www.youtube.com/results?search_query=Advanced+Learning+Model+deep+machine+ML YouTube search...]
 
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[https://www.google.com/search?q=Advanced+Learning+Model+deep+machine+ML ...Google search]
 
[https://www.google.com/search?q=Advanced+Learning+Model+deep+machine+ML ...Google search]
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[https://www.youtube.com/results?search_query=ai+Machine+Learning YouTube]
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[https://www.quora.com/search?q=ai%20Machine%20Learning ... Quora]
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[https://www.google.com/search?q=ai+Machine+Learning ...Google search]
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[https://news.google.com/search?q=ai+Machine+Learning ...Google News]
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[https://www.bing.com/news/search?q=ai+Machine+Learning&qft=interval%3d%228%22 ...Bing News]
  
 
* [[Learning Techniques]]
 
* [[Learning Techniques]]
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<b>Core:</b> four main types of learning problems in machine learning
 
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* [[In-Context Learning (ICL)]] ... [[Large Language Model (LLM)|LLM]]s understand to encode learning algorithms implicitly during their training processes
 
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* [[PRIMO.ai#Supervised|Supervised Learning]]
 
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** [https://en.wikipedia.org/wiki/Deductive_classifier Deductive Inference | Wikipedia]
 
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* [[PRIMO.ai#Unsupervised|Unsupervised Learning]]
 
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* [[PRIMO.ai#Reinforcement Learning (RL)|Reinforcement Learning (RL)]]
 
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<b>Hybrid:</b> drawing from unsupervised and supervised learning
 
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* [[PRIMO.ai#Semi-Supervised|Semi-Supervised Learning]]
 
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** [https://en.wikipedia.org/wiki/Inductive_reasoning Inductive Learning | Wikipedia]
 
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** [https://en.wikipedia.org/wiki/Transduction_(machine_learning) Transductive Learning | Wikipedia]
 
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* [[PRIMO.ai#Self-Supervised|Self-Supervised Learning]]
 
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* [https://en.wikipedia.org/wiki/Multiple_instance_learning Multi-Instance Learning | Wikipedia]
 
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<b>Other Techniques:</b>
 
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* [[Deep Learning]]
 
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* [[Transfer Learning]] a model trained on one task is re-purposed on a second related task
 
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** [[Text Transfer Learning]]
 
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** [[Image/Video Transfer Learning]]
 
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* [[Few Shot Learning]]
 
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* [[Ensemble Learning]]
 
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* [[Multi-Task Learning (MTL)]]
 
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* [[Apprenticeship Learning - Inverse Reinforcement Learning (IRL)]]
 
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* [[Imitation Learning]]
 
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* [[Simulated Environment Learning]]
 
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* [[Lifelong Learning]] - Catastrophic Forgetting Challenge
 
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* [[Neural Structured Learning (NSL)]]
 
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* [[Meta-Learning]]
 
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* [[Online Learning]]
 
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* [[Human-in-the-Loop (HITL) Learning]] / Active Learning
 
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* [[Decentralized: Federated & Distributed]] Learning
 
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Machine learning (ML) is a field devoted to understanding and building methods that let machines "learn" – that is, methods that leverage data to improve computer performance on some set of tasks. It is seen as a broad subfield of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. - [https://en.wikipedia.org/wiki/Machine_learning#History_and_relationships_to_other_fields Machine learning | Wikipedia]
 
Machine learning (ML) is a field devoted to understanding and building methods that let machines "learn" – that is, methods that leverage data to improve computer performance on some set of tasks. It is seen as a broad subfield of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. - [https://en.wikipedia.org/wiki/Machine_learning#History_and_relationships_to_other_fields Machine learning | Wikipedia]

Revision as of 12:39, 28 April 2023

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Machine learning (ML) is a field devoted to understanding and building methods that let machines "learn" – that is, methods that leverage data to improve computer performance on some set of tasks. It is seen as a broad subfield of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. - Machine learning | Wikipedia

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