Optimizing User Engagement Through Rule-Based Analysis
This project employed a rule-based approach to maximize conversions and logins by analyzing user engagement patterns, demonstrating my ability to deliver data-driven solutions.
This project employed a rule-based approach to maximize conversions and logins by analyzing user engagement patterns, demonstrating my ability to deliver data-driven solutions.
Analyzed website search queries, identified key topics, and extracted entities to improve user understanding and site performance.
Identified anomalies in kiosk performance using time series analysis, seasonal decomposition, and Isolation Forest, visualized with interactive charts.
Conducted an A/B test analysis using Bayesian methods to compare website variants, providing clear insights into conversion performance and device-specific trends.
This project uses Python, pandas and OpenAI to analyze user feedback from Excel files, classify the feedback into relevant topics, and determine the sentiment of the responses.
This project automates EDA using Python and GPT-4, providing quick insights, identifying issues, and making recommendations.
A web scraper that extracts detailed review data from Trustpilot, with an option to translate the reviews into a language of your choice.