Confusion Matrix, Accuracy, Precision, Recall & F1 Score Explained I Machine Learning скачать в хорошем качестве

Confusion Matrix, Accuracy, Precision, Recall & F1 Score Explained I Machine Learning

Learn how to evaluate your Machine Learning models using simple and powerful metrics — Confusion Matrix, Accuracy, Precision, Recall, and the F1-Score! In this beginner-friendly video, we’ll break down each concept using easy examples and visuals, so you can understand how models are judged and improved. You’ll learn: ✅ What is a Confusion Matrix? ✅ How to calculate Accuracy (Correct Predictions / Total Predictions) ✅ What are Precision and Recall (with examples)? ✅ What is F1-Score and why it’s important? ✅ Simple step-by-step example (e.g., predicting spam emails or pass/fail) ✅ Real-world interpretation of these metrics in AI and Data Science 🎓 Perfect for: Students, Data Science beginners, and anyone learning Machine Learning Model Evaluation. 📌 Watch till the end to understand why accuracy isn’t always enough! notes link on confusion matrix - https://www.pmexpertinc.com/l/confusi... #ConfusionMatrix #MachineLearning #ModelEvaluation #PrecisionRecall #F1Score #Accuracy