Learn essential machine learning concepts in this comprehensive lecture covering fundamental principles, feature vector representation, binary linear classification methods, and the perceptron algorithm. Explore how to transform raw data into meaningful feature vectors, understand the basics of binary classification problems, and master the perceptron learning algorithm - one of the earliest and most influential neural network models. Gain practical insights into machine learning foundations while building a strong theoretical understanding of how these algorithms work to classify data points into distinct categories.