文件名称：Coursera_Machine_learning_Stanford
文件大小：25.44MB
文件格式：ZIP
更新时间：2024-04-20 11:38:22
Python
Coursera机器学习斯坦福大学
【文件预览】：
Coursera_Machine_learning_Stanford-main
----(Ex7)_Unsupervised_learning_AND_PCA_algorithm()
--------data()
----(Ex2)_CostFunct_GradDescent_Regularization()
--------PredictFunction.py(478B)
--------data()
--------gradientDescent.py(2KB)
--------Test_command.py(127B)
--------FeatureMapping.py(553B)
--------Main.py(3KB)
--------Main_regularization.py(3KB)
--------CostFunction.py(2KB)
--------Activation_function.py(230B)
--------plotData.py(620B)
----(Ex3)_Multi_classification_non-linear_cost()
--------data()
--------main_NN.py(2KB)
--------oneVsAll.py(2KB)
--------displayData.py(735B)
--------main.py(2KB)
--------lrCostFunction.py(868B)
--------predict.py(2KB)
--------Sigmoid.py(228B)
----README.md(37B)
----(Ex6)_Support_Vector_Machine_algorithmm()
--------main_email_spam.py(4KB)
--------plotBoundary.py(2KB)
--------data()
--------note.txt(1KB)
--------SVM_kernels_param.py(2KB)
--------processEmail.py(2KB)
--------main_SVM_decision_boundary.py(4KB)
--------gaussianKernel.py(1KB)
----(Ex4)_Neural_Network_model_implementation()
--------data()
--------checkNNGradient.py(2KB)
--------initializeWeight.py(1024B)
--------nnCostFunction.py(4KB)
--------displayData.py(735B)
--------main.py(5KB)
--------predict.py(492B)
--------Sigmoid.py(328B)
----(Ex5)_Upgrade_Neural_network_model()
--------polyLearningCurve.py(2KB)
--------linearRegCost.py(680B)
--------polyMappingFeature.py(888B)
--------data()
--------trainLinearReg.py(845B)
--------learningCurve.py(1KB)
--------validationCurve.py(975B)
--------main.py(7KB)