[Google_Bootcamp_Day5]

Parameters W and B

Vectorized Implementation

Intuition about deep representation

Building blocks of deep neural networks

Forward and Backward propagation

• Forward propagation for layer l

• Backward propagation for layer l

• Summary

Hyperparameters

• Parameters : W[1], b[1], W[2], b[2], …
• Hyperparameters
  • learning rate
  • number of iterations
  • number of hidden layers
  • number of hidden units
  • choice of activation functions
  • momentum
  • mini-batch size
  • regularization
  • etc …

Final review for forward and backward propagation

[Source] https://www.coursera.org/learn/neural-networks-deep-learning