Using Machine Learning and Data Analysis for Social Issues with Peter York

Check out this episode to learn about:

  • An understanding of when to use ML and data science in a social, philanthropic, or government setting to make better decisions.
  • How to use data that has already been collected, and discovering what other data should be collected and analyzed.
  • Getting comfortable with probability over certainty in our research and analysis

Resources/links:

https://bctpartners.com

https://www.linkedin.com/in/peter-york-544042b/

Summary:

Peter York is a Partner at BCT Partners and leads the Data Analytics Team. He uses machine learning, statistical programming, and predictive/prescriptive analytics to create models to evaluate and improve the effectiveness of social programs for clients in the government, non-profit and corporate sectors. He has a book on the topic of evaluation for philanthropists – “Funder’s Guide to Evaluation: Leveraging Evaluation to Improve Nonprofit Effectiveness”.

In this episode of the Roboticist, Peter York talks about when and how to use machine learning and data science to make better decisions regarding social problems.



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