My projects include data science projects like a customer churn prediction system, an adaptive anomaly detection system, analyzing google play reviews and data extraction and web scraping projects. Here is some of my selected projects.
Customer Churn Prediction System
In this project I built a systems that predicts which customers churn (leave) the company and my best model got 90% accuracy. the dataset is for customers of a telecom company and each customer has 21 features that I’ve used in my prediction system
prediction results (my best model predicts churn with 90% accuracy)
Analyzing Google Play Store Apps and Reviews
In this project, I did a comprehensive analysis of the Android app market by comparing over ten thousand apps in Google Play across different categories. I’ll look for insights in the data to devise strategies to drive growth and retention
Family and Game apps have the highest market prevalence.
We find that the majority of top rated apps range from 2MB to 20MB
Adaptive Anomaly Detection System
The project goal was to build a general purpose adaptive anomaly detection system for time-series IOT sensor data. I helped research different anomaly detection methods and we eventually used half-space trees algorithm
algorithm prediction for the sensor outdoors
algorithm prediction for the sensor indoors
Web Scraping Restaurant Reviews
Implemented a web scrapper that takes in the link of the restaurant page and number of review pages and creates a csv file with reviews data like review title, review body, rating and date.
user reviews stored in csv file