Difference between revisions of "Mixture Models; Gaussian"
m |
|||
Line 2: | Line 2: | ||
|title=PRIMO.ai | |title=PRIMO.ai | ||
|titlemode=append | |titlemode=append | ||
− | |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 | + | |
+ | <!-- Google tag (gtag.js) --> | ||
+ | <script async src="https://www.googletagmanager.com/gtag/js?id=G-4GCWLBVJ7T"></script> | ||
+ | <script> | ||
+ | window.dataLayer = window.dataLayer || []; | ||
+ | function gtag(){dataLayer.push(arguments);} | ||
+ | gtag('js', new Date()); | ||
+ | |||
+ | gtag('config', 'G-4GCWLBVJ7T'); | ||
+ | </script> | ||
}} | }} | ||
[http://www.youtube.com/results?search_query=Gaussian+Mixture+clustering YouTube search...] | [http://www.youtube.com/results?search_query=Gaussian+Mixture+clustering YouTube search...] | ||
Line 10: | Line 19: | ||
* [[AI Solver]] | * [[AI Solver]] | ||
** [[...cluster]] | ** [[...cluster]] | ||
− | |||
* [http://en.wikipedia.org/wiki/Mixture_model#Gaussian_mixture_model Mixture model | Wikipedia] | * [http://en.wikipedia.org/wiki/Mixture_model#Gaussian_mixture_model Mixture model | Wikipedia] | ||
Revision as of 21:14, 7 July 2023
YouTube search... ...Google search
a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without requiring that an observed data set should identify the sub-population to which an individual observation belongs. The following are examples described in Wikipedia:
- A financial model
- House prices
- Topics in a document
- Handwriting recognition
- Assessing projectile accuracy (a.k.a. circular error probable, CEP)
- Direct and indirect applications
- Predictive Maintenance
- Fuzzy image segmentation
Parameter estimation and system identification
- Expectation maximization (EM)
- Markov chain Monte Carlo
- Moment matching
- Spectral method
- Graphical Methods
- Other methods
- A simulation