Supervised Learning: Regression and Classification

In this lesson, we will learn Supervised Learning. Labeled data, features, targets, regression, classification, binary and multi-class classification, prediction output, and real business examples will be explained in simple language. ## Lesson objective In this lesson, we will learn Supervised Learning. In the previous lesson, we covered ML workflow and data preparation. We explained business problem, target variable, feature selection, data collection, data grain, data cleaning, missing values, encoding, scaling, train/test split, and data leakage.