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🚀 Introducing CleanXo – The Future of Automated Data Cleaning! 🚀 We all know the frustration of messy, inconsistent data slowing down analysis. What if you could clean and prepare your data in under 10 minutes—without manual effort? That’s exactly

Which ai tool help us to sort the garbage waste ?

"I'm building an automated data cleaning platform, CleanXo, that simplifies the entire data preprocessing pipeline. It will automatically detect and handle outliers (Z-score, IQR, Isolation Forest), perform feature engineering, generate insights with

I think the only way to beat procrastination is being consistent which in itself is the biggest hurdle in nearly everyone's life, what do you think is the solution?

What’s Your Biggest Challenge? 🤔 Early-stage entrepreneurs face different challenges every day. What’s your biggest hurdle? 💼 Fundraising? 🚀 Scaling? Or 💡 Finding Product-Market Fit? Let us know in this poll! #StartupChallenges #FounderJourney

looking for experienced Data Engineers/Data Analysts(2+ work years) to immediately join our India Team (Gurgaon with Hybrid model) Skills Required: SQL, Python, Pyspark, Azure Databricks, Azure DevOps, Building Data Pipelines, Data Warehousing, Dat

AI TOOLS TO CHECKOUT 📝 Sincero: Make feedback easy using AI. https://sincero.io/ ⭐ Indigo: Build custom AI tools and workflows to supercharge your team's productivity. https://www.getindigo.ai/ 👀 Agentplace: A platform for creating interactive

Proud Milestones with CleanXo! Post Body: Today, I want to share some achievements in my journey building CleanXo, my automated data science platform! Here’s what I’ve accomplished so far: Designed the full vision for CleanXo: from data cleaning t

You can always tell the difference between those who dream and those who do. The doers aren’t waiting for the perfect moment—they’re taking messy action every day. If you want results, stop waiting for the stars to align and start aligning your ac

Food for thought. Instead of building AI models/agents/RAGs, why not build for AI. There is a dearth of auxiliary products and services for AI development such as benchmarking, training environments, data cleaning, synthetic data generation etc. But