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RBM with DL4J for Deep Learning

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신동 강
신동 강

RBM (Restricted Boltzmann Machine) with DL4J (Deep Learning for Java) , code for mathematics and physics

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RBM with DL4J for Deep Learning ujava.org 10th Deep Learning Workshop 2015-07-25 www.idosi.com CEO 강신동 Shindong KANG (주)지능도시
www.idosi.comujava.org
www.idosi.comspaceapi.org
www.idosi.comDL4J (Deeplearning4j, Deep Learning for Java)
www.idosi.comHopfield Network
www.idosi.comBoltzmann Machine
www.idosi.comRBM (Restricted Boltzmann Machine)
www.idosi.comGibbs Sampling and Contrastive Divergence
www.idosi.comIris Iris setosa Iris virginicaIris versicolor Sepal length (꽃받침) Sepal width Petal length (꽃잎) Petal width
www.idosi.comIris Data set
www.idosi.comRBM code of DL4J
www.idosi.comRBM execution with CUDA
www.idosi.comlayer of DL4J (real neuron layer)
www.idosi.comNeuralNetConfiguration
www.idosi.comNeuralNetConfiguration.Builder
www.idosi.comGaussian function
www.idosi.comVisibleUnit.GAUSSIAN
www.idosi.comy = 1 + e^x
www.idosi.comy = log (x)
www.idosi.comReLU (Rectified Linear Unit)
www.idosi.comSoftplus function
www.idosi.comActivation Functions Graph
www.idosi.comNoisy ReLU & Leaky ReLU
www.idosi.comHiddenUnit.RECTIFIED
www.idosi.comiteration
www.idosi.comiteration
www.idosi.comweightInit
www.idosi.comEnum WeightInit
www.idosi.comUniformDistribution
www.idosi.comMSE (Mean Squared Error)
www.idosi.comRMSE (Root Mean Squared Error)
www.idosi.comEntropy of Thermodynamics 1862 Clausius S = Q/T 1865 Clausius dS = dQ / T
www.idosi.comMicrostates for Boltzmann's Entropy
www.idosi.comBoltzmann's Entropy Equation
www.idosi.comThe change in entropy
www.idosi.comCalculation Entropy for Process
www.idosi.comLogarithm for very big number and very small number
www.idosi.comlogarithm of chemistry pH
www.idosi.comLoss Function
www.idosi.comLoss Function
www.idosi.comMSE's defect
www.idosi.comCross Entropy Error
www.idosi.comRegularization
www.idosi.comL2 coefficient for regularization L2 is used only when regularization(true) L2 is for how much the regularization should count.
www.idosi.comHessian Matrix for BFGS
www.idosi.comBFGS
www.idosi.comLimited-memory BFGS
www.idosi.comMomentum (운동량)
www.idosi.comMomentum in physics
www.idosi.comMomentum in Deep Learning
www.idosi.comMomentum Learning Rule
www.idosi.cominterface Model
www.idosi.cominterface Layer
www.idosi.comLayer.Type
www.idosi.cominterface hierarchy
www.idosi.comLayerFactories
www.idosi.comScoreIterationListener
www.idosi.cominterface Model.fit()
www.idosi.comRBM : Early epochs of training
www.idosi.comRBM : Late epochs of training 7학년일반
www.idosi.comTarget Value & Test Value Target Test T T F F TT TF FT FF Not for RBM (RBM is unsupervised learning)
www.idosi.comPrecision (정확률) Target Test T T F F TT TF FT FF TT TT + FT
www.idosi.comRecall (재현률) Target Test T T F F TT TF FT FF TT TT + TF
www.idosi.comAccuracy (정확도) Target Test T T F F TT TF FT FF TT + FF TT + TF + FT + FF
www.idosi.comMean of Velocity 4 km/h 6 km/h
www.idosi.comMean of Velocity 4 km/h 6 km/h V (km/h) = 2L km L km 4 km/h + L km 6 km/h = 2 1 4 + 1 6 = 4.8 km/h
www.idosi.comHarmonic Mean
www.idosi.comF1 score 2 x Precision x Recall Precision + Recall P 1 R 1 + 2 1
Thank you ! (주)지능도시 Intelligent City Ltd. 강신동 Shindong KANG www.idosi.com ceo@idosi.com

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