Please find out the document for AI, ML, NLP, Neural Network computer vision and etc only APPLE iOS.

1. AI foriOS:
General-Purpose Machine Learning
Libraries
Library Algorithms
Languag
e
Licens
e
Code
Dependenc
y manager
AIToolbox
 Graphs/Trees
o Depth-firstsearch
o Breadth-firstsearch
o Hill-climbsearch
o BeamSearch
o Optimal Pathsearch
 Alpha-Beta(game tree)
 GeneticAlgorithms
 ConstraintPropogation
 LinearRegression
 Non-LinearRegression
o parameter-delta
o Gradient-Descent
o Gauss-Newton
 LogisticRegression
 Neural Networks
o multiple layers,several
non-linearitymodels
o on-line andbatch
training
o feed-forwardorsimple
recurrentlayerscan be
mixedinone network
o LSTM networklayer
implemented - needs
more testing
o gradientcheckroutines
 SupportVectorMachine
 K-Means
 Principal ComponentAnalysis
 Markov DecisionProcess
o Monte-Carlo(every-visit,
Swift
Apach
e 2.0
GitHu
b

2. Library Algorithms
Languag
e
Licens
e
Code
Dependenc
y manager
and first-visit)
o SARSA
 Single andMultivariate Gaussians
 Mixture Of Gaussians
 Model validation
 DeepNetwork
o Convolutionlayers
o Poolinglayers
o Fully-connectedNN
layers
dlib
 DeepLearning
 SupportVectorMachines
 Reduced-rankmethodsforlarge-
scale classificationandregression
 Relevance vectormachinesfor
classification andregression
 A MulticlassSVM
 Structural SVM
 A large-scale SVM-Rank
 An online kernel RLSregression
 An online SVMclassification
algorithm
 Semidefinite MetricLearning
 An online kernelizedcentroid
estimator/noveltydetectorand
offline supportvectorone-class
classification
 Clusteringalgorithms:linearor
kernel k-means,Chinese
Whispers,andNewman
clustering
 Radial BasisFunctionNetworks
 Multi layerperceptrons
C++ Boost GitHub
FANN
 MultilayerArtificial Neural
Network
 Backpropagation(RPROP,
Quickprop,Batch,Incremental)
C++
GNU
LGPL
2.1
GitHub Cocoa Pods

3. Library Algorithms
Languag
e
Licens
e
Code
Dependenc
y manager
 Evolvingtopologytraining
lbimproved
k-nearestneighborsandDynamicTime
Warping
C++
Apach
e 2.0
GitHub
MAChineLearni
ng
 Neural Networks
o Activationfunctions:
Linear,ReLU, Step,
sigmoid,TanH
o Cost functions:Squared
error,Cross entropy
o Backpropagation:
Standard,Resilient(a.k.a.
RPROP).
o Trainingbysample or by
batch.
 Bag of Words
 Word Vectors
Objectiv
e-C
BSD 3-
clause
GitHub
MLKit
 LinearRegression:simple,ridge,
polynomial
 Multi-LayerPerceptron,&
Adaline ANN Architectures
 K-MeansClustering
 GeneticAlgorithms
Swift MIT GitHub Cocoa Pods
Mendel
Evolutionary/geneticalgorithms Swift ? GitHub
multilinear-
math
 Linearalgebraand tensors
 Principal componentanalysis
 Multilinearsubspace learning
Swift
Apach
e 2.0
GitHub Swift
Package

4. Library Algorithms
Languag
e
Licens
e
Code
Dependenc
y manager
algorithmsfordimensionality
reduction
 Linearand logisticregression
 Stochasticgradientdescent
 Feedforwardneural networks
o Sigmoid
o ReLU
o Softplusactivation
functions
Manager
OpenCV
 Multi-LayerPerceptrons
 Boostedtree classifier
 decisiontree
 ExpectationMaximization
 K-NearestNeighbors
 LogisticRegression
 Bayesclassifier
 Randomforest
 SupportVectorMachines
 StochasticGradientDescentSVM
classifier
 Grid search
 Hierarchical k-means
 Deepneural networks
C++
3-
clause
BSD
GitHub Cocoa Pods
Shark
 Supervised:
o Lineardiscriminant
analysis(LDA)
o Fisher–LDA
o Linearregression
o SVMs
o FF NN
o RNN
o Radial basisfunction
networks
o Regularizationnetworks
o Gaussianprocessesfor
regression
C++
GNU
LGPL
GitHub Cocoa Pods

5. Library Algorithms
Languag
e
Licens
e
Code
Dependenc
y manager
o Iterative nearest
neighborclassification
and regression
o Decisiontrees
o Randomforest
 Unsupervised:
o PCA
o RestrictedBoltzmann
machines
o Hierarchical clustering
o Data structuresfor
efficientdistance-based
clustering
 Optimization:
o Evolutionaryalgorithms
o Single-objective
optimization(e.g.,CMA–
ES)
o Multi-objective
optimization
o Basic linearalgebraand
optimizationalgorithms
YCML
 GradientDescent
Backpropagation
 ResilientBackpropagation
(RProp)
 Extreme LearningMachines
(ELM)
 ForwardSelectionusing
Orthogonal LeastSquares(for
RBF Net),alsowiththe PRESS
statistic
 BinaryRestrictedBoltzmann
Machines(CD & PCD)
 Optimizationalgorithms:
o GradientDescent (Single-
Objective,
Unconstrained)
o RPropGradientDescent
Objectiv
e-C
GNU
GPL
3.0
GitHub

6. Library Algorithms
Languag
e
Licens
e
Code
Dependenc
y manager
(Single-Objective,
Unconstrained)
o NSGA-II(Multi-Objective,
Constrained)
KalvarLin's
libraries
 ios-KRHebbian-Algorithm-
HebbianTheory
 ios-KRKmeans-Algorithm- K-
Meansclusteringmethod.
 ios-KRFuzzyCMeans-Algorithm-
FuzzyC-Means,the fuzzy
clusteringalgorithm.
 ios-KRGreyTheory - Grey
Theory / Grey systemtheory-
basedmodelsintime series
prediction
 ios-KRSVM- SupportVector
Machine and SMO.
 ios-KRKNN - kNN
implementation.
 ios-KRRBFNN - Radial basis
functionneural networkandOLS.
Objectiv
e-C
MIT GitHub