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

4.0 (2)
24 learners

What you'll learn

This course includes

  • 4.5 hours of video
  • Certificate of completion
  • Access on mobile and TV

Course content

1 modules • 34 lessons • 4.5 hours of video

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

34 lessons • 4.5 hours
  • Train/Dev/Test Sets (C2W1L01)12:05
  • Bias/Variance (C2W1L02)08:47
  • Basic Recipe for Machine Learning (C2W1L03)06:22
  • Regularization (C2W1L04)09:43
  • Why Regularization Reduces Overfitting (C2W1L05)07:10
  • Dropout Regularization (C2W1L06)09:26
  • Understanding Dropout (C2W1L07)07:05
  • Other Regularization Methods (C2W1L08)08:24
  • Normalizing Inputs (C2W1L09)05:31
  • Vanishing/Exploding Gradients (C2W1L10)06:08
  • Weight Initialization in a Deep Network (C2W1L11)06:12
  • Numerical Approximations of Gradients (C2W1L12)06:36
  • Gradient Checking (C2W1L13)06:35
  • Gradient Checking Implementation Notes (C2W1L14)05:19
  • Mini Batch Gradient Descent (C2W2L01)11:29
  • Understanding Mini-Batch Gradient Dexcent (C2W2L02)11:19
  • Exponentially Weighted Averages (C2W2L03)05:59
  • Understanding Exponentially Weighted Averages (C2W2L04)09:42
  • Bias Correction of Exponentially Weighted Averages (C2W2L05)04:12
  • Gradient Descent With Momentum (C2W2L06)09:21
  • RMSProp (C2W2L07)07:42
  • Adam Optimization Algorithm (C2W2L08)07:08
  • Learning Rate Decay (C2W2L09)06:45
  • Tuning Process (C2W3L01)07:11
  • Using an Appropriate Scale (C2W3L02)08:51
  • Hyperparameter Tuning in Practice (C2W3L03)06:52
  • Normalizing Activations in a Network (C2W3L04)08:55
  • Fitting Batch Norm Into Neural Networks (C2W3L05)12:56
  • Why Does Batch Norm Work? (C2W3L06)11:40
  • Batch Norm At Test Time (C2W3L07)05:47
  • Softmax Regression (C2W3L08)11:48
  • Training Softmax Classifier (C2W3L09)10:08
  • The Problem of Local Optima (C2W3L10)05:24
  • TensorFlow (C2W3L11)16:08

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