Data Science W207

Applied Machine Learning

3 units

Course Description

Machine learning is a rapidly growing field at the intersection of computer science and statistics concerned with finding patterns in data. It is responsible for tremendous advances in technology, from personalized product recommendations to speech recognition in cell phones. This course provides a broad introduction to the key ideas in machine learning. The emphasis will be on intuition and practical examples rather than theoretical results, though some experience with probability, statistics, and linear algebra will be important.

Course must be taken for a letter grade to fulfill degree requirements.

Prerequisites

Data Science W201 and W203. Intermediate competency in Python, C, or Java, and competency in Linux, GitHub, and relevant Python libraries; or permission of instructor. Linear algebra is recommended. MIDS students only.

Course History

Spring 2018

Instructor(s): June Andrews
Instructor(s): Yacov Salomon
Instructor(s): Zachary Alexander
Instructor(s): Zachary Alexander
Instructor(s): Lefteris Anastasopoulos
Instructor(s): Amit Bhattacharyya TBD
Instructor(s): Todd Holloway

Fall 2017

Instructor(s): Isabell Konrad
Instructor(s): Zachary Alexander
Instructor(s): Zachary Alexander
Instructor(s): Isabell Konrad
Instructor(s): Todd Holloway

Summer 2017

Instructor(s): Isabell Konrad
Instructor(s): Zachary Alexander
Instructor(s): Todd Holloway

Last updated:

October 7, 2016