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I have developed an employee attendance AI system that records the exit time along with tracking where I stored the entry and exit times in a CSV file.
The network for creativity
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Connect with clients, get discovered, and run your business 100% commission-free
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Linknest is a chrome extension which organizes your web experience to become more productive.
You can save links, screenshots and organize them into categories, and more...
Links are auto categorized based on domains and also with help of AI.
Tech Stack: React, Typescript, Python, Flask
great job👌
A sneaker reseller was losing deals because they couldn't monitor eBay listings fast enough manually. I built a Python bot that continuously monitors eBay search results for specific sneaker keywords and size filters, detects new listings or price drops below a set threshold, and sends real-time Telegram alerts the moment something matches.
The bot stores seen listings in a local SQLite database to avoid duplicate alerts, and runs on a configurable check interval (every 2–5 minutes).
Stack: Python, requests, BeautifulSoup, python-telegram-bot, schedule, sqlite3
Result: Eliminated manual hourly checks. Client received instant deal alerts and landed 4 profitable flips within the first two weeks of using the bot.
Built a retail analytics system focused on customer churn and business insights.
This project is not just a dashboard. It combines data processing, analysis, and business interpretation into one system.
What this project does:
• Analyzes retail transaction data
• Identifies patterns behind customer churn
• Highlights key drivers affecting retention
• Transforms raw data into decision-ready insights
System flow:
Raw data → Cleaning & transformation → Analysis → Insight generation → Dashboard
Key focus:
• Understanding why customers stop buying
• Turning data into actionable business insights
• Structuring data for reliable analysis
• Supporting retention strategy decisions
What this solves:
Customer churn directly impacts revenue.
This system helps:
• Identify at-risk customers
• Understand behavior patterns
• Support targeted retention strategies
Tools used:
Python | Pandas | SQL | Excel / Power BI
Outcome:
• Clear visibility into customer behavior
• Insight-driven approach to retention
• Structured analytics system for retail data
This is part of a larger goal to build full data systems that connect engineering, analytics, and business impact.
If you need data turned into real business insight, let’s work.
awesome work here
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