Measure carbon emissions of ML projects, in python
Date:
The environmental cost of ML has been increasing in recent years, due to its ever-increasing adoption in many software applications, as well as their size and complexity. Many parameters impact the carbon cost of a python program, such as the hardware used and the location of its execution. In this talk, we present the internals of Code Carbon, a library developed to better estimate the impact of ML projects, throughout their global life cycle.