week 14(11 -15 November)

In this week , we continued with deep learning course lecture no.2 "The neural net as a universal approximator" which includes recap of previous lecture related to perceptron and its firing condition.After that we first learned about deep layer structures,then we move on to multilayer perceptrons and how it is used to evaluate boolean expression , learning geometrical shapes and also learnt about required optimal depth for a neural network.


Another task was given to us by Sehra sir i.e. hypothesis testing and z-statistics assignment using R.There were 3-4 assignments which was supposed to be completed in 3 days.

 We also watched Danko sir's lecture no.2 .The lecture was about first understandig human level intelligence and how can we achieve that in computers.He taught us about electic models and specialized models also.

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