@datascibykashi: Today I explored how to evaluate linear regression models and understand how different features affect student placement outcomes! 🎓 ✅ Key Takeaways: • Evaluated model performance using metrics like R², MAE, and RMSE — to see how accurately the model predicts placement salaries. • Learned to interpret coefficients to understand which factors (like CGPA, internships, aptitude scores) have the strongest impact on placements. • Visualized feature importance to identify what truly drives success in campus placements! 🌟 📊 These insights help recruiters and institutions make data-driven decisions — turning numbers into opportunities. 💡 Linear regression might look simple, but when evaluated right, it’s a powerful prediction tool! #Day55 #datasciencejourney #linearregression #machinelearning #PlacementData #engineering #modelevaluation #AI #DataDriven #TechWithKashif #MLProjects #DataAnalytics #regressionmodel

Data Scientist | Kashi

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Region: PK

Sunday 26 October 2025 06:26:30 GMT