Day 24: Classification Algorithms | Logistic Regression| kNN

In this video, we dive into two essential machine learning algorithms: Logistic Regression and k-Nearest Neighbors (kNN). We explore how logistic regression works as a linear classifier, using the sigmoid function to predict probabilities, and discuss its strengths, such as simplicity and efficiency, along with its limitations like handling non-linear data.

We also unpack the working of kNN, a lazy learning algorithm, by explaining its instance-based approach and distance metrics like Euclidean and Manhattan. You'll learn its advantages, such as simplicity and flexibility, and challenges, including high computational cost during inference and sensitivity to noisy data.

#classification #machinelearning #protorialsbysaif