Week 2: Linear Classifiers, Logistic Regression, Bias-Variance Trade-off, and Regularization

Abstract

In this week, we will explore fundamental machine learning techniques that are widely used for classification tasks: Linear Classifiers and Logistic Regression. Additionally, we will cover core concepts like the Bias-Variance Trade-off and Regularization, which help in understanding the performance and generalization of machine learning models. These concepts are essential for building accurate and interpretable models that can classify data and predict outcomes in various fields. Understanding when and why to use these techniques is key to solving different types of problems in machine learning