> Do you have any favourite libraries for producing such?
For modern Deep Learning based probabilistic forecasting you can try DeepAR with parametric likelihood function [0] or Multi-Horizon Quantile RNN (non-parametric) [1]. The implementations of these models in Pytorch and MXnet are scattered all over the place.
And if you want to play with this the gluonts python library makes it very easy. It also includes some other time series models as well! I've been playing with it at work and it's enjoyable.
For modern Deep Learning based probabilistic forecasting you can try DeepAR with parametric likelihood function [0] or Multi-Horizon Quantile RNN (non-parametric) [1]. The implementations of these models in Pytorch and MXnet are scattered all over the place.
[0] https://arxiv.org/abs/1704.04110
[1] https://arxiv.org/abs/1711.11053
EDIT: formatting