Machine Learning 101
Presenter: Matt Gee
In this session, we’ll demystify core concepts in machine learning, give practical examples of how some of these methods have been applied across a variety of organizations, and walk you through some basic rules for deciding if your organization’s critical questions and available data resources are a good fit for a machine learning solution.
Topics covered during the session will include:
- A conceptual framework for mapping machine learning tasks to business problems
- The human process of machine learning
- The types of questions best suited for machine learning solutions
- Typical data resources required for machine learning solutions
- Typical actions that can be taken in response to machine learning solutions
The goal of the talk is to have participants leave with the ability to identify real opportunities to apply machine learning algorithms within their organizations. It will highlight applications in energy, education, marketing campaigns, public health, and operations, many drawn from the work of Data Science for Social Good
- Government Agencies, Non Profits, Policymakers who have heard of machine learning and AI and want to understand what it is and what can be done with it
- Data Analysts interested in helping Government Agencies and Non Profits and learning more advanced analytical tools.