These are notes for a one-semester undergraduate course on machine learning given by Prof. Miguel ́A. Carreira-Perpi ̃n ́an at the University of California, Merced.

Students in my Stanford courses on machine learning have already made several useful suggestions, as have my colleague, Pat Langley, and my teaching assistants, Ron Kohavi, Karl P …

Machine Learning Theory, also known as Computational Learning Theory, aims to understand the fundamental principles of learning as a computational process and combines tools from …

Machine learning systems automatically learn programs from data. This is often a very attractive alternative to manually constructing them, and in the last decade the use of machine learning …

The three broad categories of machine learning are summarized in Figure 3: (1) super-vised learning, (2) unsupervised learning, and (3) reinforcement learning. Note that in this class, we …

Apr 28, 2025 · In organizing this lecture note, I am indebted by the following: • S. RASCHKA ANDV. MIRJALILI, Python Machine Learning, 3rd Ed., 2019 [62].

Our main goal is to present fundamentals of linear algebra and optimization theory, keeping in mind applications to machine learning, robotics, and computer vision.