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.
This AI-powered web scraper uses natural language and vision to extract data from websites. It adapts to different page layouts, handles dynamic content, and avoids bot detection.
This project integrates OpenAI’s GPT with Google Home, enabling voice-activated interaction for a seamless smart assistant experience. I used Python, Flask, and the JOIN API to create this streamlined system.
A project to extract product data from websites by scraping the dataLayer object. It uses Python, Selenium, and Apify to automate browser interactions and find product info in the dataLayer. It also handles cookie prompts.
This scraper extracts data from WordPress sites using REST API and Selenium, delivering structured JSON output.
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.
Automated content generation in Google Sheets using OpenAI’s GPT models, enhancing efficiency and consistency.
Automated cover letter creation using web scraping, AI text generation, and Google Docs API. This project highlights my ability to integrate complex APIs and AI models to solve a real-world problem.