Hello everybody. Checking in for the first time under ELI5 (Scrapinghub), implementing Grad-CAM for neural networks.

What did you do this week?

Briefly looked into some auxiliary tools such as PyTest and mypy. Called with mentors for the first time. Discussed workflow and preparation details, such as when to call, create pull requests, and document code. Mentioned some things to do in the future - i.e. use Google Colab when need hardware to train a network, consider how to test image output, go through the technical Grad-CAM paper together. In the suborg's Slack, discussed how everyone should give updates.

What is coming up next?

Set up a recommended environment: PyCharm IDE, Jupyter notebooks for manual testing, one virtualenv for development and tox for testing on other environments. Enable recent libraries such as CUDA 9 on my local NVIDIA hardware. Install, use, and look over source code of existing Grad-CAM implementations. Look over and do the relevant parts of the recommended course at http://cs231n.stanford.edu/. Briefly learn tox (make sure the project's tox config works for me locally) and look into Sphinx very briefly.

Did you get stuck anywhere?

No specific issues yet, just overall a bit slow to start looking into the actual topic of the project- Grad-CAM.

Thank you for reading!

Tomas Baltrunas