Can we beat the state of the art from 2013 with only 0.046% of training examples?

My results

I applied transfer learning which is a technique where you take a model trained to carry out some other though similar task and you retrain it to do well on the task at hand.

What happened

This is thoroughly unexpected. The technique that I used is covered in the first lecture of Practical Deep Learning for Coders, part 1. In the Jupyter notebook provided with the course, it takes 7 lines of code to perform transfer learning.


The results are staggering. I didn’t have to apply data augmentation, didn’t adjust the learning rate nor had to care about regularization. I didn’t even test different architectures — this is literally the first one I tried.



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Radek Osmulski

Radek Osmulski


I ❤️ ML / DL ideas — I tweet about them / write about them / implement them. Recommender Systems at NVIDIA