Difference between revisions of "Learning Techniques"

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|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS  
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|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools  
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[http://www.youtube.com/results?search_query=Advanced+Learning+Model+deep+machine+ML YouTube search...]
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[https://www.youtube.com/results?search_query=ai+Advanced+Learning+Technique+Model YouTube]
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[http://www.google.com/search?q=Advanced+Learning+Model+deep+machine+ML ...Google search]
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[https://www.quora.com/search?q=ai%20Advanced%20Learning%20Technique%20Model ... Quora]
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[https://www.google.com/search?q=ai+Advanced+Learning+Technique+Model ...Google search]
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[https://news.google.com/search?q=ai+Advanced+Learning+Technique+Model ...Google News]
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[https://www.bing.com/news/search?q=ai+Advanced+Learning+Technique+Model&qft=interval%3d%228%22 ...Bing News]
  
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* [http://machinelearningmastery.com/types-of-learning-in-machine-learning/ 14 Different Types of Learning in Machine Learning | Jason Brownlee - Machine Learning Mastery]  
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* [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]]
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* [[PRIMO.ai#Natural Language|Natural Language]]
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* [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Grok]] | [https://x.ai/ xAI] ... [[Groq]] ... [[Ernie]] | [[Baidu]] ... [[DeepSeek]]
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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]  
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* [[Large Language Model (LLM)#Multimodal|Multimodal Machine Learning]]  
  
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<b>Core:</b> four main types of learning problems in machine learning
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<b>Learning Problems:</b>
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* [[In-Context Learning (ICL)]] ... [[Context]] ... [[Causation vs. Correlation]] ... [[Autocorrelation]] ... [[Out-of-Distribution (OOD) Generalization]] ... [[Transfer Learning]]
 
* [[PRIMO.ai#Supervised|Supervised Learning]]
 
* [[PRIMO.ai#Supervised|Supervised Learning]]
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** [https://en.wikipedia.org/wiki/Deductive_classifier Deductive Inference | Wikipedia]
 
* [[PRIMO.ai#Unsupervised|Unsupervised Learning]]
 
* [[PRIMO.ai#Unsupervised|Unsupervised Learning]]
 
* [[PRIMO.ai#Reinforcement Learning (RL)|Reinforcement Learning (RL)]]
 
* [[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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<b>Hybrid Learning Problems:</b>
 
 
* [[PRIMO.ai#Semi-Supervised|Semi-Supervised Learning]]
 
* [[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]
 
* [[PRIMO.ai#Self-Supervised|Self-Supervised Learning]]
 
* [[PRIMO.ai#Self-Supervised|Self-Supervised Learning]]
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* [http://en.wikipedia.org/wiki/Multiple_instance_learning Multi-Instance Learning]
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* [https://en.wikipedia.org/wiki/Multiple_instance_learning Multi-Instance Learning | Wikipedia]
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<b>Statistical Inference:</b>
 
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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.
 
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* Inductive Learning
 
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* Deductive Inference
 
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* Transductive Learning
 
  
  
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<b>Learning Techniques:</b>
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<b>Other Techniques:</b>
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* [[Active Learning]]
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* [[Deep Learning]]
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* [[Online Learning]]
 
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* [[Text Transfer Learning]]
 
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* [[Image/Video Transfer Learning]]
 
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* [[Few Shot Learning]]
 
 
* [[Transfer Learning]] a model trained on one task is re-purposed on a second related task
 
* [[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]] ... [[Few Shot Learning#One-Shot Learning|One-Shot Learning]] ... [[Few Shot Learning#Zero-Shot Learning|Zero-Shot Learning]]
 
* [[Ensemble Learning]]
 
* [[Ensemble Learning]]
 
* [[Multi-Task Learning (MTL)]]
 
* [[Multi-Task Learning (MTL)]]
 
* [[Apprenticeship Learning - Inverse Reinforcement Learning (IRL)]]
 
* [[Apprenticeship Learning - Inverse Reinforcement Learning (IRL)]]
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* [[Imitation Learning]]
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* [[Imitation Learning (IL)]]
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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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* [[Embodied AI| Action Learning ... Embodied AI]]
 
* [[Simulated Environment Learning]]
 
* [[Simulated Environment Learning]]
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* [[Lifelong Learning]] - Catastrophic Forgetting Challenge
 

Latest revision as of 05:58, 30 January 2025

YouTube ... Quora ...Google search ...Google News ...Bing News

Core: four main types of learning problems in machine learning

Hybrid: drawing from unsupervised and supervised learning


Other Techniques:

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