Applied Machine Learning for Social Good

Tutorial: Applied Machine Learning for Social Good

Rakshit Agrawal (University of California, Santa Cruz, USA)

Date: Thursday, October 17
Time: 1-5 pm

Abstract:

This tutorial will focus on topics around using machine learning methods for social good. This includes knowledge of some basics in machine learning, and focusing on how to identify societal challenges, define problems, find solutions using machine learning and methods to deploy those solutions in the real world.

The tutorial will base itself on the course at University of California, Santa Cruz on Applied ML for Social Good (https://sites.google.com/ucsc.edu/cmps290t-spring-2019/). This would include case studies, coding samples, and a full run through building an ML based solution for one of the target problems under the United Nations Global Goals.

Approach:

First we will introduce the framework of Identification, Definition, Solution and Deployment. Then we will discuss the identification using UN Global Goals. This will then be used in definition using targets from Global Goals. Then we will teach a Machine Learning pipeline (Gather data, Extract features, Develop model, Train and optimize, Evaluate). This pipeline will then be used on a specific problem and dataset The deployment will be taught using a client-server model The tutorial will end with additional resources to learn more on the topic.

 

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