🎉 About 🎉

In almost every field, there is a need to draw inferences from or make decisions based on data. The goal of this course is to provide an introduction to machine learning that is approachable to diverse disciplines and empowers students to become proficient in the foundational concepts and tools while working with interdisciplinary real-world data. You will learn to (a) structure a machine learning problem, (b) determine which algorithmic tools are applicable to a given problem, (c) apply those algorithmic tools to diverse, interdisciplinary data examples, (d) evaluate the performance of your solution, and (e) how to accurately interpret and communicate your results. This course is a fast-paced, applied introduction to machine learning that arms you with the basic skills you will need in practice to both conduct analyses and effectively communicate your results. Instructor: Dr. Luyao Zhang, Assistant Professor of Economics at Social Science Division and Senior Research Scientist at Data Science Research Center, Duke Kunshan University.

Mission

Part of Industry 4.0 Open Educational Resource Publication Initiatives: Series No. 6: Machine Learning for Social Science

Series No. 1: Innovate on the Internet Computer: https://ic.pubpub.org/

Series No. 2: Intelligent Economics: An Explainable AI Approach: https://ie.pubpub.org/

Series No. 3: Computational Economics: https://ce.pubpub.org/

Series No. 4: Summer Research Scholar by Sunshine: https://srs.pubpub.org/.

Series No. 5: Rising Star by Sunshine: https://rs.pubpub.org/

Diversity and Inclusion

Created collaboratively of the community, by the community, and for the community

Connect

A call for collaboration among university faculties, students, staff, and beyond