TransferLearning Image Classification model for Clothing Category
In this Ipnyb , I'm going to build a model that can classify the Clothing Attribute Dataset which can be found at https://purl.stanford.edu/tb980qz1002 by the Category label. This is an image recognition and classification task . This dataset has only 1800 samples , out of which around 1100 samples have non - Nan values .
Therefore , the approach to be followed will be : Use Transfer learning ( in this case VGGNet16 trained on Imagenet data ) to learn weights for our features
Train our features against a classifier . Our choice of classifier here is SVM
There are two ipython notebooks , one with augmented data and one without . We see , in this case that the data without augmentation does much better as compared to the data with augmentatiom