Personally, I focused on the work of the design review report. After reviewing more related works and analyzing the ingredients that might result in high recognition accuracy and lower false cases, I built a table of ingredient candidates that we might count as the final 10 items that we will be recognizing and relating recipes to. The table is attached in the post.
In addition, I learned about the current popular recommendation systems and how to build them from scratch. I followed these tutorials: https://www.toptal.com/algorithms/predicting-likes-inside-a-simple-recommendation-engine and https://www.analyticsvidhya.com/blog/2018/06/comprehensive-guide-recommendation-engine-python/ to help me design the algorithms for a small scale recommendation system.
I am in the right place of the schedule we planned and not behind. For the deliverables for next week, we will first finish up the report together, and next personally I will be focusing on grabbing the recipes related to the candidates listed in the table and finalize our 10 items on the list and 30 recipes as well.
