Have you ever looked a long list of machine learning algorithms and wondered where to get started? And how to apply them to your problem in energy, agriculture, water or any other clean technology sector?
If that sounds like you, sign up here for our online course on getting started with machine learning in clean technology. We'll talk about the basic concepts in machine learning, discuss applications in the clean technology sector, identify the algorithms that are most commonly applied to problems in water, agriculture, energy and other clean tech sectors and get started using these algorithms. Since we believe that the best learning comes when we solve real-world problems, our hands-on problem will be building a machine learning model to understand and identify different land uses using existing software.
Gayathri is an award-winning scientist who has been pioneering the integration of clean technology and data science since 2003. She worked in large organizations, including Facebook, Argonne National Laboratory, several Silicon Valley startups and is the recipient of numerous national and international awards. As a scientist, her work has been recognized by the US National Academies of Science and Engineering for innovative environmental research and she was invited by the White House in 2014 to participate in the conference on innovation in clean technology and big data. As an engineer and data scientist, she built the data infrastructure, including data pipelines, dashboards and algorithms, for several startups. She received her PhD in Environmental Engineering from the University of Illinois at Urbana-Champaign and her Bachelors in Civil Engineering from BITS, Pilani, India.