*Logistic Regression* part-2 | Industry Relevant AI ML Course

📞 Want 1:1 personal mentorship with me? Book a session on Topmate here: [https://topmate.io/sonuyadav5504] Whether you're a student, working professional, developer, or complete beginner, this detailed module will build a strong foundation for the rest of the course. By the end, you’ll know how to clean data the right way and build leakage-free ML pipelines that generalize well. 0:01 Decision Boundary in Logistic Regression 0:17 Probability Output to Final Class Prediction 0:54 Threshold Selection for Binary Classification 1:24 Custom Decision Boundary Explained 1:54 Regularization in Logistic Regression 2:07 L1 and L2 Regularization Recap 3:30 Evaluation Metrics for Classification 3:55 Confusion Matrix Introduction 4:50 What is Confusion Matrix? 5:50 Confusion Matrix Example with 100 Samples 7:46 Accuracy Calculation from Confusion Matrix 8:51 True Positive False Positive True Negative False Negative 11:26 Accuracy Formula Explained 11:53 Precision and Recall Explained 12:24 Precision Formula and Intuition 13:20 Recall Formula and Intuition 14:29 Precision Recall Tradeoff 15:18 Cancer Detection Example for Precision and Recall 16:31 Effect of Threshold on Precision and Recall 18:49 When Precision Matters vs When Recall Matters 19:36 Recall Example in Cancer Detection 20:34 Precision Example in Email Spam Detection 21:30 F1 Score Explained 21:40 Harmonic Mean of Precision and Recall 22:28 When to Use F1 Score 22:55 ROC Curve and AUC Introduction 23:22 True Positive Rate and False Positive Rate 24:25 ROC Curve Intuition 25:13 Random Classifier Baseline in ROC Curve 26:20 Area Under Curve Explained 27:14 AUC Score Interpretation 28:37 Class Imbalance Problem 28:51 Why Accuracy Fails on Imbalanced Data 29:53 Resampling Techniques for Class Imbalance 30:11 Oversampling Explained 31:05 Undersampling Explained 32:17 Threshold Change for Imbalanced Classes 34:42 Class Weighted Loss Explained 35:40 Weighted Loss Function Intuition 37:30 Credit Card Fraud Detection Imbalance Example 38:03 Logistic Regression Final Summary 38:24 Notes and WhatsApp Group Information 38:30 End of Lecture 🔗 Connect with Me: ---------------------------------- Instagram (YouTube) →   / sonuyadav_iitdelhi   Instagram (Personal) →   / sonuyadav5504   👉 Join WhatsApp Channel: https://whatsapp.com/channel/0029Vb7b... WhatsApp Group → https://chat.whatsapp.com/HjGuZZr07Uu... ---------------------------------- #ArtificialIntelligence #AIML #MachineLearning #DeepLearning #NLP #ComputerVision #GenerativeAI #LLM #AIforBeginners #TechEducation #FreeCourse #SonuYadav