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Curious about ROC Curve and ROC-AUC in machine learning but finding it confusing? This video is here to simplify these concepts for you. 💡 Why It Matters in ML: ROC Curve and ROC-AUC are like a report card for our machine learning models, showing us how well they perform. 🔗 Resources: Code - https://colab.research.google.com/dri... Notebook PDF : https://drive.google.com/file/d/1Ql1v... ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in ============================ 📱 Grow with us: CampusX' LinkedIn: / campusx-official CampusX on Instagram for daily tips: / campusx.official My LinkedIn: / nitish-singh-03412789 Discord: / discord 👍If you find this video helpful, consider giving it a thumbs up and subscribing for more educational videos on data science! 💭Share your thoughts, experiences, or questions in the comments below. I love hearing from you! ⌚Time Stamps⌚ 00:00 - Intro 01:15 - Why ROC Curve? 16:05 - Confusion Matrix 20:57 - True Positive Rate (TPR) - Benefit 28:05 - False Positive Rate (FPR) - Cost 38:12 - ROC Curve 43:12 - Different Cases 01:01:28 - Code Example 01:05:37 - AUC/ROC ✨ Hashtags✨ #MachineLearningBasics #ROCCurveExplained #ROCAUCinML #SimplifiedTech #LearnWithData