The Clean Tech Data Scientist's Essential Toolkit
One of the most amazing things to happen in the last few years has been the explosion of open source software tools that can perform an incredible number of tasks at minimal cost. This is especially true for data scientists who use a wide variety of free tools to do their job. In the clean tech field however, there is usually a need to use a combination of open source and pre-existing legacy software. This is mainly because the functionality of open source tools has not yet caught up with the existing tools for several clean tech applications. Data Scientists and engineers looking to use machine learning, artificial intelligence and remote sensing tools to solve problems in water, agriculture, energy or other clean tech fields need to use a combination of different software and tools to obtain the best results.
So, what would constitute the essential elements of the clean tech data scientist’s tool kit?