Tackling Climate Change with Machine Learning
In the first of our two-part conversation on machine learning in climate science, we talked about the main challenges in using machine learning in earth and environmental science. Today, let’s talk about why we go through the effort of using these tools in clean technology when they require a significant investment in understanding and modifying them. Why use machine learning? Three main reasons - 1) Do it better 2) Do it faster 3) Find unexplained trends or patterns. 1) Do it better : Last time we talked about the challenges of using machine learning in solving problems in clean technology. And that’s still true for unmodified, off-the shelf models. However, there’s a huge opportunity for scientists and engineers who are interested in understanding and adapting these models to make them work effectively with all the other tools in the tool box! Let’s look at one such adaptation where machine learning algorithms can be used in concert with physics based models to generate more a...