Part - 03 | Understanding ROC Curve and AUC in Machine Learning

Welcome to our comprehensive tutorial on AUC (Area Under the Curve) and ROC (Receiver Operating Characteristic) curves in machine learning! Whether you're a beginner or an experienced data scientist, this video will help you understand these crucial evaluation metrics.
In this video, you'll learn:
Introduction to ROC Curves:
What is a ROC curve?
The significance of the true positive rate (sensitivity) vs. the false positive rate (1-specificity).
How to interpret different points on the ROC curve.
Understanding AUC:
What is AUC and why is it important?
The relationship between AUC and the ROC curve.
Interpreting AUC values and what they indicate about model performance.
Creating ROC Curves:
Step-by-step guide to plotting ROC curves using Python and popular libraries like sklearn.
Example with a real-world dataset to visualize the ROC curve.

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[@mohammedabduladnan145]

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[@SubhamkumarSingh-wq4pf]

Nice Explain

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