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Created a Python utility script to process and clean structured data automatically, reducing manual effort.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Really nice concept and clean app design. The marketplace and community-focused experience look very thoughtfully put together. Great work! 🚀
Feed The Flock — community platform for trading homegrown/homemade goods and sustainable-living education.
You Will Get Apollo + LinkedIn Sales Navigator B2B Leads, Verified Emails & Direct Phone Numbers.
Need targeted B2B leads with accurate contact information for your sales or outreach?
What You Provide:
✔Target industry / niche
✔Location
✔Company size or other filters
✔Decision-maker titles
✔Or your Apollo / LinkedIn Sales Navigator search link
What I Do:
I research and qualify the right companies and decision-makers, then enrich the prospects with:
✔Verified business emails
✔Direct phone / mobile numbers
✔LinkedIn profiles
✔Job titles
✔Company information
I also verify, clean, and remove duplicates before delivery.
What You Receive:
Company • Contact Name • Job Title • LinkedIn • Verified Email • Direct Phone • Website
Why Choose Me:
✓ Targeted B2B research
✓ Multiple data sources
✓ Manual data checking
✓ Email & contact verification
✓ Clean, organized, outreach-ready data
Tools: Apollo • LinkedIn Sales Navigator • Lusha • ContactOut • SalesQL • Google Sheets
Ready to Get Started?
Send me your target requirements or Apollo / Sales Navigator search link, and I can start with a small sample.
good work
An end-to-end machine learning project for detecting fraudulent financial transactions using the PaySim synthetic transaction dataset.
The project focuses not only on training an XGBoost classifier, but on the complete ML journey: baseline modeling → feature engineering → hyperparameter tuning → threshold tuning → evaluation → live deployment.
