Case Study: QuackQuack

Offerings: Web & Mobile App Development , AI/ML

Quackquack cs

Company website : https://www.quackquack.in/

Company Profile

Leading Indian dating app with 14M users. 1000+ new users per day and growing. Promises verified profiles of users, Interest based matchmaking, and fake & spammer free app

Problem

Classifying user profile information into vague, spam, infomercial, genuine. Manual verification of user profiles (5 employees, 35k/month) is error prone, tedious and boring

Solution

  • Hamon developed machine learning techniques to create models that can help detect bad actors from genuine users and improve the usability of the app.
  • Hamon was able to come in and quickly develop the right machines learning models and help QuackQuack

Result

82% Accuracy rate in detecting spams based on available models and timeframe of the project. The company was able to remove human curators

Technologies

SciKit Learn, Pandas, Jupyter Notebook, AWS EC2, Python webstack (Flask, PostgreSQL, SQL Alchemy)