Lecture 6 | Training Neural Networks I

Lecture 6 | Training Neural Networks I

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Stanford University School of Engineering • 82K views

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Math topics:
_Vector_calculus_##Vector calculus##_Gradient_##Gradient##_Euclidean_vector_##Euclidean vector##_Vector_field_##Vector field##_Elementary_mathematics_##Elementary mathematics##_Linearity_##Linearity##_Equality_(mathematics)_##Equality (mathematics)##_Subtraction_##Subtraction##_Function_(mathematics)_##Function (mathematics)##_Identity_function_##Identity function##_Exponentials_##Exponentials##_Exponential_function_##Exponential function##_Hyperbolic_function_##Hyperbolic function##_Normal_distribution_##Normal distribution##_Numbers_##Numbers##_0_(number)_##0 (number)##_1_(number)_##1 (number)##_Negative_number_##Negative number##_Model_selection_##Model selection##_Cross-validation_(statistics)_##Cross-validation (statistics)##_Hyperparameter_optimization_##Hyperparameter optimization##_Loss_function_##Loss function
Other topics:
_Artificial_neural_networks_##Artificial neural networks##_Rectifier_(neural_networks)_##Rectifier (neural networks)##_Activation_function_##Activation function##_Artificial_neural_network_##Artificial neural network##_Backpropagation_##Backpropagation##_Sigmoid_function_##Sigmoid function##_Summary_statistics_##Summary statistics##_Standard_deviation_##Standard deviation##_Mean_##Mean##_Variance_##Variance##_Machine_learning_##Machine learning##_Statistical_classification_##Statistical classification##_Machine_learning_##Machine learning##_Convolutional_neural_network_##Convolutional neural network
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