There are two time series and we need to predict one based on the other.
The idea behind it is: the input series is very noisy, whereas the output is smoothen (apparently there is no obvious pattern). This happens for multiple locations, so we need to check which model fits best each location.
We have a preference for Python, but R is fine as well.
33 freelancers are bidding on average $178 for this job
Hi, I am interested in your project. I am Python and Machine Learning specialist, certified by Freelancer. I fully understand your requirements and I am sure I can help you. Let's discuss details by chat.
Dear. I am a professional in applied mathematics. I have many experiences in ML(SVM/clustering/ANN/regression/...) We can discuss details via chat. I wait for you now. Thanks.
Hello, I have briefly read the description on apply-machine-learning-techniques , and I can deliver as per the requirements however I need us to discuss for more clarity on the details, deadline and budget as well.