Pie & AI is a series of deeplearning.ai meetups independently hosted by community groups. This event is hosted by Deep Learning Graz.
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Abstract: Contrastive loss terms allows someone to learn good representations in DeepLearning without labels based on the data alone. This can be used in a later stage f.e. to train classifiers with a greatly (about 100 times) reduced need in labels. F.e. the xent loss learns by data augmentation and negative sampling good representations in an unsupervised manner. We show how to use this loss and train a network, present choices for data augmentation, discuss where it’s useful or not, and present some use cases the presenters worked on with the term.