This course introduces key machine learning models and their applications. Students will learn how machines can automatically discover patterns from data and use these patterns to make predictions or decisions. The topics include an overview of supervised learning, linear models, kernel methods, neural networks, an overview of unsupervised learning, clustering, dimensionality reduction, and an introduction to deep learning. Upon completion of this course, students should be able to apply various machine learning models to solve real-world problems.
- Teacher: pengw, Wang Peng