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Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization (Course 2 of the Deep Learning Specialization)

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Regularization (C2W1L04)

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Why Regularization Reduces Overfitting (C2W1L05)

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Bias/Variance (C2W1L02)

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Basic Recipe for Machine Learning (C2W1L03)

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Weight Initialization in a Deep Network (C2W1L11)

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Numerical Approximations of Gradients (C2W1L12)

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Dropout Regularization (C2W1L06)

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Vanishing/Exploding Gradients (C2W1L10)

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Train/Dev/Test Sets (C2W1L01)

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Other Regularization Methods (C2W1L08)

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Normalizing Inputs (C2W1L09)

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Understanding Dropout (C2W1L07)

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Mini Batch Gradient Descent (C2W2L01)

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Gradient Checking Implementation Notes (C2W1L14)

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Gradient Checking (C2W1L13)

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