Read my full write-up with visualizations on my website galenballew.github.io
Or check out the article on Medium.
The Challenge: Some of the most advanced convolutional neural networks are available with their weights already trained. This starting state can produce enormous leverage for your next image classification task. This project shows how the bottlenecking technique can be employed to significantly increase the training speed for the repurposed network.
The Toolkit:
- TensforFlow
- scikit-learn
- Keras
- numpy
- D3.js
The Results: Check out my website for the D3 visualization of training accuracy/loss for the different networks.