This podcast episode introduces logistic regression, a classification algorithm that uses a linear regression algorithm to predict the probability of an input belonging to a particular class. It explains the concepts of logits, argmax, sigmoid function, error function, gradient descent, and composability in machine learning. The episode also highlights the importance of understanding linear and logistic regression as the building blocks of machine learning and their role in deep learning.