深度學習神課斯坦福 cs231n deep learning open course from Standford 英文教學版(DVD9一片裝 此片售價200元)



深度學習神課斯坦福cs231ndeeplearningopencoursefromStandford英文教學版(DVD9一片裝此片售價200元)-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=軟體名稱:深度學習神課斯坦福cs231ndeeplearningopencoursefromStandford英文教學版(DVD9一片裝此片售價200元)語系版本:英文教學版光碟片數:單片裝破解說明:系統支援:Windows7/XP/Vista軟體類型:電腦教學硬體需求:PC更新日期:2017-11-28官方網站:中文網站:軟體簡介:銷售價格:$200元-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=　軟體簡介:　cs231n可以說是深度學習最好的公開課，這個版本是spring2017。新鮮出爐，歡迎各位品嚐ComputerVisionhasbecomeubiquitousinoursociety,withapplicationsinsearch,imageunderstanding,apps,mapping,medicine,drones,andself-drivingcars.Coretomanyoftheseapplicationsarevisualrecognitiontaskssuchasimageclassification,localizationanddetection.Recentdevelopmentsinneuralnetwork(aka「deeplearning」)approacheshavegreatlyadvancedtheperformanceofthesestate-of-the-artvisualrecognitionsystems.Thiscourseisadeepdiveintodetailsofthedeeplearningarchitectureswithafocusonlearningend-to-endmodelsforthesetasks,particularlyimageclassification.Duringthe10-weekcourse,studentswilllearntoimplement,trainanddebugtheirownneuralnetworksandgainadetailedunderstandingofcutting-edgeresearchincomputervision.Thefinalassignmentwillinvolvetrainingamulti-millionparameterconvolutionalneuralnetworkandapplyingitonthelargestimageclassificationdataset(ImageNet).Wewillfocusonteachinghowtosetuptheproblemofimagerecognition,thelearningalgorithms(e.g.backpropagation),practicalengineeringtricksfortrainingandfine-tuningthenetworksandguidethestudentsthroughhands-onassignmentsandafinalcourseproject.MuchofthebackgroundandmaterialsofthiscoursewillbedrawnfromtheImageNetChallenge.課程名稱：Lecture1：計算機視覺的概述、歷史背景以及課程計劃Lecture2：圖像分類算法Lecture3：損失函數和優化（lossFunctionandoptimization）Lecture4：神經網絡Lecture5：卷積神經網絡（CNN）Lecture6：如何訓練神經網絡ILecture7：如何訓練神經網絡IILecture8:深度學習軟件基礎Lecture9：卷積神經網絡架構（CNNArchitectures）Lecture10：循環神經網絡（RecurrentNeuralNetworks）Lecture11：檢測與分割（DetectionandSegmentation）Lecture12：可視化和理解（VisualizingandUnderstanding）Lecture13：生成模型（GenerativeModels）Lecture14：強化學習（ReinforcementLearning）Lecture15：深度學習高效的方法和硬件（EfficientMethodsandHardwareforDeepLearning）Lecture16：對抗性樣本和對抗性訓練（AdversarialExamplesandAdversarialTraining）-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=