Welcome to my collection of data science projects completed during the TripleTen Data Science Bootcamp.
Each project highlights skills in Python, SQL, hypothesis testing, data visualization, and machine learning.
- Video Game Sales Analysis
- Customer Churn Prediction
- Coin Toss App (Streamlit)
- Car Ads Dashboard
- Mobile Plans: Usage & Revenue Analysis
- Model Comparison (Classification)
- Data Cleaning & Missing Data Visualization
(Sprint 5 – Integrated Project 1)
Goal: Explore global video game sales to identify regional trends and platform performance.
Skills Used: pandas, matplotlib, hypothesis testing, data visualization
Repository: View Project
(Sprint 7 – Machine Learning in Business)
Goal: Predict telecom customer churn using logistic regression and random forest models.
Skills Used: scikit-learn, feature engineering, model evaluation
Repository: View Project
(Sprint 4 – Software Development Tools)
Goal: Develop and deploy an interactive app simulating coin flips with live visual stats.
Skills Used: Streamlit, Python, data visualization, user interaction
Repository: View Project
(Sprint 6 – Data Collection and Storage)
Goal: Build an interactive dashboard to analyze car listings and pricing trends.
Skills Used: Python, SQL, visualization, dashboard design
Repository: View Project
(Sprint 3 – Statistical Data Analysis)
Goal: Examine user behavior and revenue performance for two mobile plans.
Skills Used: pandas, matplotlib, statistical testing
Folder: mobile_plans_eda
(Sprint 7 – Machine Learning in Business)
Goal: Evaluate performance of multiple classification models for predictive accuracy.
Skills Used: scikit-learn, cross-validation, metrics (F1, AUC)
Folder: model_comparison
(Sprint 5 – Integrated Project 1)
Goal: Prepare datasets for analysis by identifying and addressing missing or anomalous values.
Skills Used: pandas, data cleaning, visualization
Folder: data_cleaning
⭐️ Each project demonstrates hands-on experience applying data science techniques across exploratory analysis, statistical testing, and machine learning.