Photo by Nicholas Doherty on Unsplash

My final project in the Metis data science bootcamp was on forecasting hourly electricity demand. We barely touched on time series during the bootcamp, but my strong desire to work in clean energy after graduation required me to get acquainted with the dark horse of data science. As I discuss in great detail in another blog post, improving energy demand forecasts with machine learning is a key step in modernizing the electric grid, transitioning to renewables, and ultimately mitigating the effects of climate change.

Time series is a wicked beast of a subject, and I learned a lot while grinding…


A handmade sign of planet Earth with black background and white lettering saying “One World” in all caps. Likely used at a protest.
A handmade sign of planet Earth with black background and white lettering saying “One World” in all caps. Likely used at a protest.
Photo by Markus Spiske on Unsplash

Or rather, “Tackling Climate Change with Machine Learning.” Today I will recap some of my favorite sections of the much-publicized article written by David Rolnick and others way back in 2019. You know, the long, long ago. These folks are at the forefront of AI research to mitigate the effects of climate change, and more people should pay attention to their important work.

The Role of Data Scientists, Entrepreneurs, and Technologists

Mike Jehl

Data science, clean energy, civic tech, rock climbing.

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