Evaluation Metrics | Classification | Fraud Detection | Accuracy, Precision, Recall, F1-score

Why is your Machine Learning model failing even with 98% accuracy? In this Machine Learning model evaluation tutorial, you’ll learn how to evaluate a classification model properly using Python, Scikit-learn and Google Colab. We make fraud detection project and learn why accuracy alone is not enough to judge a Machine Learning model. In this tutorial, you will learn How to choose the right evaluation metric for your ML problem We’ll apply everything to a fraud detection problem using Python + Pandas + Scikit-learn + Google Colab. Next tutorial: Overfitting & Underfitting — Why does an ML model perform well on training data but fail on new data? Colab notebook link: https://drive.google.com/file/d/1X4JU...