We'll help you pick.
Give us one restaurant you love. We'll find places you'll probably love too.
From filter coffee before work to biryani after midnight.
Slow mornings.
Strong coffee.
Crispy.
Golden.
Iconic.
Because Bangalore
loves biryani too.
Work.
Chill.
Repeat.
BangaBites combines multiple signals to find restaurants that actually fit your preferences.
North Indian
Banashankari
⭐ 4.0
BangaBites is an intelligent restaurant recommendation system built to help food lovers discover restaurants based on what they already enjoy.
BangaBites combines restaurant similarity, ratings, popularity, location and budget preferences to create personalized restaurant recommendations.
BangaBites is a machine-learning based restaurant recommendation project built around Bengaluru's diverse food scene. It takes a restaurant a user already likes and identifies other restaurants with similar characteristics.
The recommendation system combines multiple signals instead of relying only on ratings.
Matches restaurants by food type and preparation style.
Uses Bayesian-weighted ratings rather than raw scores.
Filters and boosts restaurants in your preferred Bengaluru locality.
Considers vote counts and overall dining activity.
Scores restaurants that fit your cost-for-two preference.
A combined final score used to rank your shortlist.
How BangaBites turns restaurant data into recommendations.
BangaBites does not simply return the restaurants with the highest ratings. It combines multiple signals into a final recommendation score.
BANGABITES SCORE
Bengaluru is more than a technology city. It is a city of filter coffee mornings, dosa breakfasts, café evenings, biryani nights and endless food discoveries.
Find any restaurant from the Bengaluru dataset to use as a starting point.
Discover similar restaurants using content-based machine learning.
Filter recommendations within a preferred Bengaluru neighbourhood.
Set a minimum star rating to only see quality-assured picks.
Set a maximum cost for two so every result fits your wallet.
Restaurants are ranked by a combined recommendation score, not just ratings.
Jump to a restaurant's Zomato page whenever a valid URL is available.
AI & Data Science Student • Developer • Data & ML Enthusiast
BangaBites was designed and developed by Ankit Govind Pardeshi as a machine-learning and data-driven restaurant recommendation project focused on Bengaluru's food ecosystem.
"I enjoy building practical projects that combine data, machine learning and thoughtful user experiences."
BangaBites brings together restaurant data and machine learning to turn thousands of choices into a shortlist that feels easier to explore.