Difference between revisions of "Repositories & Other Algorithms"
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| + | {{#seo: | ||
| + | |title=PRIMO.ai | ||
| + | |titlemode=append | ||
| + | |keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS | ||
| + | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | ||
| + | }} | ||
[http://www.youtube.com/results?search_query=open+source+code+sourceforge+github+artificial+intelligence+deep+learning Youtube search...] | [http://www.youtube.com/results?search_query=open+source+code+sourceforge+github+artificial+intelligence+deep+learning Youtube search...] | ||
| + | [http://www.google.com/search?q=open+source+code+sourceforge+github+deep+machine+learning+ML+artificial+intelligence ...Google search] | ||
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| + | * [[Git - GitHub and GitLab]] | ||
| + | * [[Libraries & Frameworks]] | ||
Algorithms with Wikipedia pages... | Algorithms with Wikipedia pages... | ||
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* [http://en.wikipedia.org/wiki/Rule-based_machine_learning Rule-based machine learning] | * [http://en.wikipedia.org/wiki/Rule-based_machine_learning Rule-based machine learning] | ||
* [http://en.wikipedia.org/wiki/Skill_chaining Skill chaining] | * [http://en.wikipedia.org/wiki/Skill_chaining Skill chaining] | ||
| − | * [ | + | * [http://en.wikipedia.org/wiki/Sparse_PCA Sparse PCA] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/State%E2%80%93action%E2%80%93reward%E2%80%93state%E2%80%93action State–action–reward–state–action] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Stochastic_gradient_descent Stochastic gradient descent] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/Structured_kNN Structured kNN] |
| − | * [ | + | * [http://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding T-distributed stochastic neighbor embedding] ... [[Embedding]] |
| − | + | * [http://en.wikipedia.org/wiki/Temporal_difference_learning Temporal difference learning] | |
| − | + | * [http://en.wikipedia.org/wiki/Wake-sleep_algorithm Wake-sleep algorithm] | |
| − | + | * [http://en.wikipedia.org/wiki/Weighted_majority_algorithm_(machine_learning) Weighted majority algorithm (machine learning)] | |
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Latest revision as of 18:56, 26 June 2023
Youtube search... ...Google search
Algorithms with Wikipedia pages...
- Almeida–Pineda recurrent backpropagation
- ALOPEX
- Backpropagation
- Bootstrap aggregating
- CN2 algorithm
- Constructing skill trees
- Dehaene–Changeux model
- Diffusion map
- Dominance-based rough set approach
- Dynamic time warping
- Error-driven learning
- Evolutionary multimodal optimization
- Expectation–maximization algorithm
- FastICA
- Forward–backward algorithm
- GeneRec
- Genetic Algorithm for Rule Set Production
- Growing self-organizing map
- HEXQ
- Hyper basis function network
- IDistance
- K-nearest neighbors algorithm
- Kernel methods for vector output
- Kernel principal component analysis
- Leabra
- Linde–Buzo–Gray algorithm
- Local outlier factor
- Logic learning machine
- LogitBoost
- Manifold alignment
- Minimum redundancy feature selection
- Mixture of experts
- Multiple kernel learning
- Non-negative matrix factorization
- Online machine learning
- Out-of-bag error
- Prefrontal cortex basal ganglia working memory
- PVLV - primary value learned value
- Q-learning
- Quadratic unconstrained binary optimization
- Query-level feature
- Quickprop
- Radial basis function network
- Randomized weighted majority algorithm
- Reinforcement learning
- Repeated incremental pruning to produce error reduction (RIPPER)
- Rprop
- Rule-based machine learning
- Skill chaining
- Sparse PCA
- State–action–reward–state–action
- Stochastic gradient descent
- Structured kNN
- T-distributed stochastic neighbor embedding ... Embedding
- Temporal difference learning
- Wake-sleep algorithm
- Weighted majority algorithm (machine learning)
