Ideas for model to predict wind speed in a local kitesurfing spot We have a sensor in a local kite spot that captures real time wind speed, we've found that we can somewhat predict if there's going to be &quot;good&quot; wind by looking at different forecast models and weather conditions.
I think it should be easy to train a model that takes input from different forecast models as well as real time data to predict with higher accuracy the speed in the spot.
Do you think this would be too crazy? if not how would you suggest I approach building this, having no experience with machine learning at all
Predicting weather is very complex, so it's unlikely you'll improve upon any predictions from services like WindFinder.
I would first try to prove that predictions from a service like WindFinder are inaccurate, i.e. collect historical predictions and compare it your recordings of sensor data at your local position.
After this, encode your heuristic model which allows you to predict the &quot;good wind&quot; based on other sources into code, but with current information I'm not sure where the ML fits in, rather it seems to just be aggregating sensor &amp; weather site information into a single metric.