Code for NN Training and Prediction - IT/Computer Science Assignment Help

Assignment Task :

Write down code from scratch for an N layer neural network for multiclass classification.
You must
1. Use Vectorization
2. Just use iterations (no need for convergence condition)
3. Multi-class problem - use softmax and cross-entropy 
4. Code should work for any number of hidden layers provided as input 
5. Add L2 regularization 
6. Split data into training and test. Plot your error curves for training and validation errors (cost
and accuracy)
1. For different number of hidden layers (1, 2, 3, 4, 5, etc) - 2 points
2. For different alpha values (choosing the "best" hidden layer configuration from the previous item) 
3. For different values of lambda (regularization parameter) (lambda = 0 means no regularization, lambda > 0 means you are regularizing). "lambda" is a reserved keyword in python so use some other variable names say to denote it.
Briefly discuss which configuration worked best and why you think it worked well. Why other configurations did not work as well.
 

Additional Points:
1) Follow the lecture notes for your reference
2) The cost function to be used is

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