The second lecture from the Machine Learning course series of lectures. This lecture discusses ROC metric for evaluating machine learning model's performance. In particular, two ways of building ROC are discussed. A link to my github (https://github.com/skyfallen/MachineLearningPracticals) with practicals that I have designed for this course in both R and Python. I can share keynote files, contact me via e-mail: firstname.lastname@example.org.