Ranjan's blog

Before going into Deep learning, one of the major concepts is needed tensor calculus. To be more specific we need to know how to differentiate a scaler/vector/matrix with respect to vector/matrix. In this blog I am going discuss that will be needed in to understand Deep learning.

There are some basic concepts which are very important to understand machine learning.

• Kullback–Leibler(KL) divergence
• Transformation of random variables
• Maximum Likelihood Estimation

Suppose you are doing research in a particular image processing problem using DeepLearning and you are successful with solving that problem. Next you want to deploy it very quickly. Here I will discuss the steps in details, the problem I face and the the tricks to overcome that. Mainly API serverside coding with django.

To Write

To Write

Problems for Mathematical Olympiad

Evalution of optimizer

and