The Accuracy Trap Every ML Interview Asks About

99% accuracy sounds perfect — until you find out your model never actually catches what it's supposed to catch. In this video, I break down two connected interview questions: why accuracy fails on imbalanced datasets, and what precision and recall actually measure, including when to prioritize one over the other. If you're prepping for ML/AI interviews and want to actually understand concepts instead of reciting definitions, this is for you. 🔑 What you'll learn: 🔹️Why a model can have 99% accuracy and still be useless 🔹️What precision and recall actually mean, in plain terms 🔹️When to prioritize precision vs recall, with real examples Subscribe — I'm sharing my ML interview prep journey as I go, one concept at a time. #MachineLearning #PrecisionRecall #MLInterview #AIInterview #DataScience #InterviewPrep #LearnAI