Minified recommendation system - with warm start.
- Update the food_form.xlsx with more food items, user details and food features
Assigned to: [@psymbio,@someoneelse] Status: [NOTDONE] Due: [22/7/24]
Food: Create features like cuisine type (Italian, Chinese, Mexican, Indian, American, etc.), tastes (sweet, sour, spicy, bitter, etc.), cost, nutritional information (calories, protein, carbohydrates, fats, fiber, sugars, sodium, vitamins and minerals), allergens (e.g., nuts, dairy, gluten), dietary preferences (vegetarian, vegan, gluten-free, halal, kosher, low-carb, low-fat), serving size (small, medium, large). Users: Create features like demographic information (age, gender, are they vegetarian?). Add some more useful features to this and finalize this with the team.
- Create the Google form for this. It's easy to copy-paste from Excel to create multiple-choice checkboxes. Share the edit link with everyone. Discuss and finalize the form and send it out to people to collect the data. Assigned to: [@someoneelse] Status: [NOTDONE] Due: [22/7/24]
- Create the recsys algorithm from scratch
- Based on user demographics create some extra rules
- Test the system
- Document the code, formulae, etc.
- Read papers: https://arxiv.org/pdf/1507.08439
Assigned to: [@psymbio] Status: [BLOCKED - need real data to train] Due: [27/7/24]
- Make the APIs (login, signup, food recommendation) - thinking FastAPI
- DB connection, populate DB with fake data - thinking Postgres
Assigned to: [@psymbio] Status: [NOTDONE] Due: [30/7/24]
- Wireframe design
- Login, signup
- Main page
- Setup the backend
- Setup the frontend
- Communicate to the frontend team about how the APIs work
- Integrate the backend and the frontend
- Select template and share the PPT with everyone
- Make the PPT (add to it as and when the works done)
- Create the architecture diagram for the code
Assigned to: [@everyone] Status: [NOTDONE] Due: [27/7/24]