ds401深度學習tensorflow課程大綱

近年來，深度學各領域的應用上突飛猛進，也受到大家廣泛的矚目，但如何從零開部分:(1)介紹深度學習中的各種要素，以及(2)動手建立你的第一個深度學習模WhatisdeeplearningandwhataresuccessfulWhyisdeeplearningdifferentfrommachinelearningandtraditionalstatistics?Whataretheessentialconceptsandskillsthata“deeplearner”shouldpossess?Whythisclasswillhelpyousucceedinyourtechnicalcareer(jobhuntingorstartingupyour ,etc)?FinallyweintroducetheagendaofDS401:classcontentsandprojectFeedforwardNeuralNetworkFeedforwardNeuralNetwork所需要的概念及技術簡介下兩堂課內容:FNN,CNN,RNN具體理論課程安排FunctionalityofdeepImportantapplicationsofdeepDatasetrepresentationandBackwardTraining,testingandcrossFeedforwardNeuralNetworkNetworkActivationLoss項目課程安排TensorFlow+KerasonFeedforwardNeuralNetwork(trainFeedforwardNeuralNetworkembeddingspacewordConvolutionalNeuralNetwork(trainFeedforwardNeuralNetworkStochasticgradientembeddingspacewordUnderstandingembeddingspacebyusingwordembeddingasApplicationsfromwordVariantstotrainawordConvolutionalNeuralNetworkWhyCNNforConvolutionallayerZeroChannels:greyscalev.s.colorfulMax示范對資料及模型的操作：inTensorFlowKerasGetfamiliarwithMNISTPreprocessFNNinTensorFlowKerasDesignnetworkstructure:towerv.s.Changeactivationfunction:isReLUtheSelectlossDropout:when,whereandhowL1andL2Regularization:whatarethefeedforwardneuralnetworkwordGetfamiliarwithtextrepresentationandnewsDesignandtrainaExaminethewordConvolutionalNeuralNetwork所需要的概念及技能講解深度學習進階模型：RecurrentNeuralNetwork(RNN)RNNConvolutionalNeuralNetworkSelectionofthenumberandsizeofVariants:InceptionVariants:ResVariants:DEVISEforcotrainingimagesandRecurrentNeuralNetworkNetworkwithGradientdiminishandGatedRecurrentUnitLongShortTermMemoryCNNinTensorFlowKerasRevisitMNISTDesignconvolutio