Linear and Logistic RegressionIntroduces linear and logistic regression, covering parametric models, multi-output prediction, non-linearity, gradient descent, and classification applications.
Introduction to Data ScienceIntroduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Linear Models: Part 2Covers linear models, binary and multi-class classification, and logistic regression with practical examples.
