I default to Prophet (formerly FBProphet) for my work [which is business-y timeseries data], curious what others are doing.
Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
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Re: Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
#2Prophet, statsmodels, tf.keras for RNNs.
Re: Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
#3I was told to start with XGBoost. Is Prophet better?
Re: Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
#4Re: Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
#5I'll often use tensorflow probability's time series package.
Re: Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
#6I was told to start with XGBoost. Is Prophet better?
Xgboost is a classifier for tabular data, prophet is for time series prediction. They are different use cases, though you can likely massage xgboost to do time series prediction if you really wanted to. So the question of which is better is "it depends"
Re: Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
#7Sktime is the best toolkit for time series out there. It provides a sklesrn like API for many models and modules for validating, metrics for evaluating and all that sklearm jazz.
Besides that, I also like statsmodels as the docs are pretty good.
Re: Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
#8PyTorch for recurrent nets (TensorFlow would work too).
Re: Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
#9It really depends on what is the goal.
Get some forecasts quick => FB Prophet. It's not as good as they'd have you believe, but it's fast and analysts can play with it to some extent.
Outlier detection => Hand-rolled C++ ETS framework.
Multilevel predictions and/or more complex tasks => That's where neural models start to have the edge, but at that point it's a costly project. I like simpler stuff to start, moving to the big guns if/when it's needed.
Re: Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
#10I was told to start with XGBoost. Is Prophet better?
Xgboost is a classifier for tabular data, prophet is for time series prediction. They are different use cases, though you can likely massage xgboost to do time series prediction if you really wanted to. So the question of which is better is "it depends"
I'm not even sure how you can get it to work on time series...