Stanford deep learning tutorial exercises on Self-Taught code, source code need to fill all places, all the full complement of the code, the handwriting recognition into the path of a database, you can run directly

Exercise6 Self-Taught Learning\computeNumericalGradient.m
..............................\display_network.m
..............................\feedForwardAutoencoder.m
..............................\initializeParameters.m
..............................\loadMNISTImages.m
..............................\loadMNISTLabels.m
..............................\minFunc\ArmijoBacktrack.m
..............................\.......\autoGrad.m
..............................\.......\autoHess.m
..............................\.......\autoHv.m
..............................\.......\autoTensor.m
..............................\.......\callOutput.m
..............................\.......\conjGrad.m
..............................\.......\dampedUpdate.m
..............................\.......\example_minFunc.m
..............................\.......\example_minFunc_LR.m
..............................\.......\isLegal.m
..............................\.......\lbfgs.m
..............................\.......\lbfgsC.c
..............................\.......\lbfgsC.mexa64
..............................\.......\lbfgsC.mexglx
..............................\.......\lbfgsC.mexmac
..............................\.......\lbfgsC.mexmaci
..............................\.......\lbfgsC.mexmaci64
..............................\.......\lbfgsC.mexw32
..............................\.......\lbfgsC.mexw64
..............................\.......\lbfgsUpdate.m
..............................\.......\.ogistic\LogisticDiagPrecond.m
..............................\.......\........\LogisticHv.m
..............................\.......\........\LogisticLoss.m
..............................\.......\........\mexutil.c
..............................\.......\........\mexutil.h
..............................\.......\........\mylogsumexp.m
..............................\.......\........\repmatC.c
..............................\.......\........\repmatC.dll
..............................\.......\........\repmatC.mexglx
..............................\.......\........\repmatC.mexmac
..............................\.......\mchol.m
..............................\.......\mcholC.c
..............................\.......\mcholC.mexmaci64
..............................\.......\mcholC.mexw32
..............................\.......\mcholC.mexw64
..............................\.......\mcholinc.m
..............................\.......\minFunc.m
..............................\.......\minFunc_processInputOptions.m
..............................\.......\polyinterp.m
..............................\.......\precondDiag.m
..............................\.......\precondTriu.m
..............................\.......\precondTriuDiag.m
..............................\.......\rosenbrock.m
..............................\.......\taylorModel.m
..............................\.......\WolfeLineSearch.m
..............................\softmaxCost.m
..............................\softmaxPredict.m
..............................\softmaxTrain.m
..............................\sparseAutoencoderCost.m
..............................\stlExercise.m
..............................\testMemory.m
..............................\minFunc\logistic
..............................\minFunc
Exercise6 Self-Taught Learning

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