Train and test a multi layer network.
- Implement a deep network from scratch
- Use of python libraries like numpy, matplotlib and tensorflow
- Better understanding of the theory of gradient descent and back propagation
- Implement a k-layer deep network from scratch, with batch noramlization and scale and shift.
- Better understanding of initialization of the parameter of network (Xavier/He/Glorot Initialization)
- Coarse Search of hyperparameter like lambda
- Open anaconda command prompt, cd to the desired lab and run:
jupyter notebook