Hi! This is a check-in for the last week of community bonding. I am writing this at the end of week 1, so I hope I still remember most of what I did!
What did you do this week?
Briefly tested out Tox and Sphinx on my machine. Made sure I can run all the environments specified in ELI5’s tox.ini: I had to apt-get some python-dev packages, and comment out the installation for xgboost 0.6a2 due to installation issues on Ubuntu. Set up a few virtualenv’s. Installed PyCharm IDE. Git clone’d existing Grad-CAM implementations for Keras and checked that they work using examples from ImageNet. Commented the source code by stepping through it with pdb. Looked at the authors’ implementation of Grad-CAM in Lua.
What is coming up next?
Week 1 tasks will begin! As scheduled I will implement Grad-CAM for images (working with Keras models). One change will be that I will make automated tests during week 2, not week 1. Instead of testing this week, I will add an image formatter so that I can get immediate feedback of the Grad-CAM algorithm implemented. There were some things that I planned to do during this week, but prioritised them for later, including: Enabling my GPU to use with ML libraries, learning about RNN’s, and setting up virtualenvwrapper/pyenv instead of plain virtualenv.
Did you get stuck anywhere?
At the end of the week I was stuck at understanding the details of Grad-CAM and how is it implemented in Keras. I wish I could’ve spent more time on learning actual Keras and doing some CNN visualisations.
Thanks for reading again!