Accuracy alone can fool you. That’s why data scientists rely on precision, recall, and F1-score to measure what truly matters. In this 7-minute video, you’ll finally see how these metrics connect: from the confusion matrix, to precision, recall, and even the F score. Each score reveals a different side of your model’s performance. Perfect for machine learning students, career switchers, or interview prep — this video is a complete walkthrough. 00:00 Intro 00:39 Confusion Matrix 01:31 Precision 02:10 Recall 03:05 Precision vs Recall 03:25 Precision recall curve 04:00 F score 04:53 When to use each 📘You'll learn: 1. What a confusion matrix really tells you 2. How to calculate precision, recall, and F1-score 3. When to optimize each (and why!) 4. How to interpret the trade-offs between them. 🧠 Watch this once, and you’ll never mix up these metrics again! 📎 Related shorts: Precision ▶️ [ Recall ▶️ [ F-score ▶️ [ Confusion Matrix prime ▶️r: 📚📚📚 Free resources mentioned:📚📚📚 F score Choice of metric and tradeoffs - #expandable-2 Visualize Accuracy, F1-score and MCC with data imbalance case scenarios @lanvu3003/when-my-data-are-imbalanced-accuracy-f1-score-or-mcc-24d9baf424)[ @lanvu3003/when-my-data-are-imbalanced-accuracy-f1-score-or-mcc-24d9baf424] Accuracy, Precision, Recall, and F1-score: Visualise F1 SCORE - )[ Precision Precision infographic by Epachamo - ( ) Google developers crash course - #precision Cool visualization and explanation by Paul Vanderlaken - Recall Try it yourself! - Deep-ml problem 52 - Recall on Wikipedia - MLU Explain - Google developers crash course - #recall Cool visualization and explanation by Paul Vanderlaken - Deep ML metric problems: #️⃣ Hashtags: #machinelearning #datascience #precision #recall #f1score #confusionmatrix #classification #mlmetrics #deeplearning #ai #modelperformance #mlinterview #dataviz #accuracy #modelvalidation #python #techcareers #mlbeginners #learnai