Getting value out of geodata with AI: convert locations to their lat and lon
At Cmotions we love to get inspired by working on projects that are just a little different than our day-to-day work, that is why we have our The Analytics Lab, where we organize our so called Project Fridays. This specific Project Friday was initiated by a question concerning wolf presence coming from a biologist. Starting with a small question and some enthusiastic colleagues, it ended up in a whole bunch of Python code, an understandable xgboost model to predict wolf presence in an area, a scientific article (please let us know if you are interested in reading this article) and a series of articles to share our approach (see links below). This article is part of that series, in which we show how we gather and prepare geographical data to use in a predictive model, visualize the predictions on a map and understand/unbox our model using SHAP.
If you want to use the notebooks that are the base of the articles in this series, check out our Cmotions Gitlab page.