Difference between revisions of "Learning Techniques"
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| − | |keywords=artificial, intelligence, machine, learning, models | + | |keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools |
| − | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | + | |
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| − | [ | + | [https://www.youtube.com/results?search_query=ai+Advanced+Learning+Technique+Model YouTube] |
| − | [ | + | [https://www.quora.com/search?q=ai%20Advanced%20Learning%20Technique%20Model ... Quora] |
| − | + | [https://www.google.com/search?q=ai+Advanced+Learning+Technique+Model ...Google search] | |
| − | + | [https://news.google.com/search?q=ai+Advanced+Learning+Technique+Model ...Google News] | |
| − | + | [https://www.bing.com/news/search?q=ai+Advanced+Learning+Technique+Model&qft=interval%3d%228%22 ...Bing News] | |
| + | * [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]] | ||
| + | * [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)#Multimodal|Multimodal Machine Learning]] | ||
| − | <b>Core:</b> | + | <b>Core:</b> 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]] | ||
* [[PRIMO.ai#Supervised|Supervised Learning]] | * [[PRIMO.ai#Supervised|Supervised Learning]] | ||
| − | ** [ | + | ** [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)]] | ||
| − | <b>Hybrid:</b> | + | <b>Hybrid:</b> drawing from unsupervised and supervised learning |
* [[PRIMO.ai#Semi-Supervised|Semi-Supervised Learning]] | * [[PRIMO.ai#Semi-Supervised|Semi-Supervised Learning]] | ||
| − | ** [ | + | ** [https://en.wikipedia.org/wiki/Inductive_reasoning Inductive Learning | Wikipedia] |
| − | ** [ | + | ** [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]] | ||
| − | * [ | + | * [https://en.wikipedia.org/wiki/Multiple_instance_learning Multi-Instance Learning | Wikipedia] |
| − | |||
| − | |||
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| + | <b>Other Techniques:</b> | ||
| + | * [[Deep 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 | ||
** [[Text Transfer Learning]] | ** [[Text Transfer Learning]] | ||
** [[Image/Video Transfer Learning]] | ** [[Image/Video Transfer Learning]] | ||
| − | * [[Few Shot Learning]] | + | * [[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)]] | ||
| − | * [[Imitation Learning | + | * [[Imitation Learning (IL)]] |
| − | |||
* [[Lifelong Learning]] - Catastrophic Forgetting Challenge | * [[Lifelong Learning]] - Catastrophic Forgetting Challenge | ||
| − | * [[ | + | * [[Neural Structured Learning (NSL)]] |
| + | * [[Meta-Learning]] | ||
* [[Online Learning]] | * [[Online Learning]] | ||
| + | * [[Human-in-the-Loop (HITL) Learning]] / Active Learning | ||
| + | * [[Decentralized: Federated & Distributed]] Learning | ||
| + | * [[Embodied AI| Action Learning ... Embodied AI]] | ||
| + | * [[Simulated Environment Learning]] | ||
Latest revision as of 07:50, 2 September 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- Artificial Intelligence (AI) ... Generative 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
