Week 4 : Last week of Community Bonding
This week I had a video meeting with my mentor Priyanshu Sinha. We discussed a lot of things and I was able to clear most of my queries.
1. I discussed how the datasets suggested earlier were not open source and hence, I would be switching to other open source options.
2. We finalized all the model compression methods that I would be trying. I will be majorly focusing on post-training methods but at the same time, I was free to experiment with compression aided methods.
3. We restructured the system architecture and decided the functionalities of the Flask application. It will run on the Raspberry Pi emulated using Qemu. Qemu will be run using a docker container. I have successfully done 3/4th of this. The integration of the Flask application is challenging and will be done later.
4. Based on the previous point, I modified my Dockerfile and created my first Merge Request.
5. I mapped out a workflow for my project. First I will begin with model training and then proceed to model compression. Then I will develop the Flask application. Finally I will integrate all the modules.
6. We also discussed that I should also read more about the papers suggested by my other mentor Saptarshi Purkayastha.
7. Next week I will begin EDA on the datasets and model training. I will also look into the Flask integration problem.
Coding period starts next week. Can't wait!
1. I discussed how the datasets suggested earlier were not open source and hence, I would be switching to other open source options.
2. We finalized all the model compression methods that I would be trying. I will be majorly focusing on post-training methods but at the same time, I was free to experiment with compression aided methods.
3. We restructured the system architecture and decided the functionalities of the Flask application. It will run on the Raspberry Pi emulated using Qemu. Qemu will be run using a docker container. I have successfully done 3/4th of this. The integration of the Flask application is challenging and will be done later.
4. Based on the previous point, I modified my Dockerfile and created my first Merge Request.
5. I mapped out a workflow for my project. First I will begin with model training and then proceed to model compression. Then I will develop the Flask application. Finally I will integrate all the modules.
6. We also discussed that I should also read more about the papers suggested by my other mentor Saptarshi Purkayastha.
7. Next week I will begin EDA on the datasets and model training. I will also look into the Flask integration problem.
Coding period starts next week. Can't wait!
Comments
Post a Comment