Machine Learning for Data Science

Catalog description

Modern computing power has enabled the development of powerful tools for uncovering complex high-dimensional relationships. The tools and methods discussed in this course are basic components of the interrelated areas known as machine learning, data science, statistics, artificial intelligence and big data. These tools include classification and regression models such as k-nearest neighbors, naive Bayes, regularized regression, ensemble methods with trees, deep neural nets, as well as unsupervised learning such as clustering and dimension reduction.