Overview / Usage

State of the art MNIST

A CNN model which achieves 99.7% accuracy. It makes use of Vgg16 model. I've used data augmentation, batch normalization, dropout, maxpooling . The model has been finetuned. Accuracy on training set = 99.42 and accuracy on validation set = 99.45. The model doesn't overfit at all. Three models have been used:

Linear model
Single dense layers
Vgg style CNN
Requirements

keras==1.2.2
Python 2.7

Dogs and cats classification

Made use of Vgg16 model(which won Imagenet competition in 2014).

Models has been finetuned in order to classify image as dog or cat.

Download data:

Test data
Training data
Acquiring this repo

$ cd ~
$ git clone https://github.com/Convnets
$ cd machine-learning-programs