Price Prediction & User-Based Restaurant Finder
Budget: ₹600 – ₹1,500 INR
I'm looking for a system that primarily focuses on predicting restaurant prices while also recommending restaurants based on user preferences.
Key Features:
- The system should have the capability of predicting prices at various restaurants. This will greatly assist users in budgeting their meals.
- It should also recommend restaurants tailored to individual user preferences. This could include factors like cuisine type, dietary restrictions, and personal taste based on past reviews.
Data Sources:
- The system will utilize existing restaurant databases as well as user reviews and ratings. Therefore, experience with data mining and machine learning on these types of datasets would be beneficial.
- Ideally, the freelancer will have experience with building similar recommendation systems, and can provide examples of their past work.
Skills and Experience Needed:
- Proficiency in Python, R or similar programming languages
- Experience with machine learning and data mining
- Familiarity with existing restaurant databases
- Ability to create user-tailored recommendations
- Experience with price prediction models
Key Features:
- The system should have the capability of predicting prices at various restaurants. This will greatly assist users in budgeting their meals.
- It should also recommend restaurants tailored to individual user preferences. This could include factors like cuisine type, dietary restrictions, and personal taste based on past reviews.
Data Sources:
- The system will utilize existing restaurant databases as well as user reviews and ratings. Therefore, experience with data mining and machine learning on these types of datasets would be beneficial.
- Ideally, the freelancer will have experience with building similar recommendation systems, and can provide examples of their past work.
Skills and Experience Needed:
- Proficiency in Python, R or similar programming languages
- Experience with machine learning and data mining
- Familiarity with existing restaurant databases
- Ability to create user-tailored recommendations
- Experience with price prediction models