Fifth week at this course is about Neural Networks

The initial topic is the detailed study about Cost Function.

Back Propagation and Forward Propagation are also explained.

The second part of this session is about Back-propagation in Practice

The lesson covers Unrolling Parameters (into vectors). Using reshape in MATLAB.

Gradient Checking is explained and also it is recommended to turn it off for training.

Random Initialization is the method used for Symmetry Breaking.

Last part of session is about putting all these together.