/ERA_V2_S5

ERA V2 Assignment 5

Primary LanguageJupyter Notebook

ERA_V2_S5

ERA V2 Assignment 5 was related to MNIST Dataset The MNIST database is a large database of handwritten digits

We created a basic model to train it

In utils.py file you will find helper functions like defining train and test transformations, train and tes functions and training and test loss and accuracy

In models.py file you will find architecture of CNN, in the output layer we have used softmax because the output labels are 10. So, when the output lables are more then 2 then its a multi-class problem so at that time we generally used softmax activation function

We have then imported this utils and models files in our S5 ipython notebook to run our whole code