Washu CSE 417T OVERVIEW This course is an introduction to machine learning, focusing on supervised learning. We will cover the mathematical foundations of learning, a number of important techniques ...

This document covers machine learning basics. The focus is on concepts and general approaches, with demonstration in R, though examples can be found for Python as well. The background assumed for the ...

Machine learning (ML) is a subfield of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computers and systems to learn from and make ...

A Brief Introduction to Machine Learning for Engineers is the entry point to machine learning for students, practitioners, and researchers with an engineering background in probability and linear ...

Abstract: This edited book comprises chapters that describe the IoT, machine learning, and blockchain technologies for renewable energy and modern hybrid power systems with simulation examples and ...

Here are some example questions here for studying for the midterm/final. Note that these are exams from earlier years, and contain some topics that will not appear in this year's exams. And some ...

machine learning, deep learning, and knowledge acquisition and representation. * If both CS 343(H) Artificial Intelligence (Honors) and CS& 363D (378H) Introduction to Data Mining (Honors) are taken, ...