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] | ||
| − | *[ | + | * [[Git - GitHub and GitLab]] |
| − | *[ | + | * [[Libraries & Frameworks]] |
| − | |||
| − | + | Algorithms with Wikipedia pages... | |
| − | + | * [http://en.wikipedia.org/wiki/Almeida%E2%80%93Pineda_recurrent_backpropagation Almeida–Pineda recurrent backpropagation] | |
| − | + | * [http://en.wikipedia.org/wiki/ALOPEX ALOPEX] | |
| − | + | * [http://en.wikipedia.org/wiki/Backpropagation Backpropagation] | |
| + | * [http://en.wikipedia.org/wiki/Bootstrap_aggregating Bootstrap aggregating] | ||
| + | * [http://en.wikipedia.org/wiki/CN2_algorithm CN2 algorithm] | ||
| + | * [http://en.wikipedia.org/wiki/Constructing_skill_trees Constructing skill trees] | ||
| + | * [http://en.wikipedia.org/wiki/Dehaene%E2%80%93Changeux_model Dehaene–Changeux model] | ||
| + | * [http://en.wikipedia.org/wiki/Diffusion_map Diffusion map] | ||
| + | * [http://en.wikipedia.org/wiki/Dominance-based_rough_set_approach Dominance-based rough set approach] | ||
| + | * [http://en.wikipedia.org/wiki/Dynamic_time_warping Dynamic time warping] | ||
| + | * [http://en.wikipedia.org/wiki/Error-driven_learning Error-driven learning] | ||
| + | * [http://en.wikipedia.org/wiki/Evolutionary_multimodal_optimization Evolutionary multimodal optimization] | ||
| + | * [http://en.wikipedia.org/wiki/Expectation%E2%80%93maximization_algorithm Expectation–maximization algorithm] | ||
| + | * [http://en.wikipedia.org/wiki/FastICA FastICA] | ||
| + | * [http://en.wikipedia.org/wiki/Forward%E2%80%93backward_algorithm Forward–backward algorithm] | ||
| + | * [http://en.wikipedia.org/wiki/GeneRec GeneRec] | ||
| + | * [http://en.wikipedia.org/wiki/Genetic_Algorithm_for_Rule_Set_Production Genetic Algorithm for Rule Set Production] | ||
| + | * [http://en.wikipedia.org/wiki/Growing_self-organizing_map Growing self-organizing map] | ||
| + | * [http://en.wikipedia.org/wiki/HEXQ HEXQ] | ||
| + | * [http://en.wikipedia.org/wiki/Hyper_basis_function_network Hyper basis function network] | ||
| + | * [http://en.wikipedia.org/wiki/IDistance IDistance] | ||
| + | * [http://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm K-nearest neighbors algorithm] | ||
| + | * [http://en.wikipedia.org/wiki/Kernel_methods_for_vector_output Kernel methods for vector output] | ||
| + | * [http://en.wikipedia.org/wiki/Kernel_principal_component_analysis Kernel principal component analysis] | ||
| + | * [http://en.wikipedia.org/wiki/Leabra Leabra] | ||
| + | * [http://en.wikipedia.org/wiki/Linde%E2%80%93Buzo%E2%80%93Gray_algorithm Linde–Buzo–Gray algorithm] | ||
| + | * [http://en.wikipedia.org/wiki/Local_outlier_factor Local outlier factor] | ||
| + | * [http://en.wikipedia.org/wiki/Logic_learning_machine Logic learning machine] | ||
| + | * [http://en.wikipedia.org/wiki/LogitBoost LogitBoost] | ||
| + | * [http://en.wikipedia.org/wiki/Manifold_alignment Manifold alignment] | ||
| + | * [http://en.wikipedia.org/wiki/Minimum_redundancy_feature_selection Minimum redundancy feature selection] | ||
| + | * [http://en.wikipedia.org/wiki/Mixture_of_experts Mixture of experts] | ||
| + | * [http://en.wikipedia.org/wiki/Multiple_kernel_learning Multiple kernel learning] | ||
| + | * [http://en.wikipedia.org/wiki/Non-negative_matrix_factorization Non-negative matrix factorization] | ||
| + | * [http://en.wikipedia.org/wiki/Online_machine_learning Online machine learning] | ||
| + | * [http://en.wikipedia.org/wiki/Out-of-bag_error Out-of-bag error] | ||
| + | * [http://en.wikipedia.org/wiki/Prefrontal_cortex_basal_ganglia_working_memory Prefrontal cortex basal ganglia working memory] | ||
| + | * [http://en.wikipedia.org/wiki/PVLV PVLV - primary value learned value] | ||
| + | * [http://en.wikipedia.org/wiki/Q-learning Q-learning] | ||
| + | * [http://en.wikipedia.org/wiki/Quadratic_unconstrained_binary_optimization Quadratic unconstrained binary optimization] | ||
| + | * [http://en.wikipedia.org/wiki/Query-level_feature Query-level feature] | ||
| + | * [http://en.wikipedia.org/wiki/Quickprop Quickprop] | ||
| + | * [http://en.wikipedia.org/wiki/Radial_basis_function_network Radial basis function network] | ||
| + | * [http://en.wikipedia.org/wiki/Randomized_weighted_majority_algorithm Randomized weighted majority algorithm] | ||
| + | * [http://en.wikipedia.org/wiki/Reinforcement_learning Reinforcement learning] | ||
| + | * [http://en.wikipedia.org/wiki/Repeated_incremental_pruning_to_produce_error_reduction_(RIPPER) Repeated incremental pruning to produce error reduction (RIPPER)] | ||
| + | * [http://en.wikipedia.org/wiki/Rprop Rprop] | ||
| + | * [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/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)] | ||
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)
