Explainable Forecasting at Scale

NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip.

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from neuralprophet import NeuralProphet
import pandas as pd

df = pd.read_csv('toiletpaper_daily_sales.csv')

m = NeuralProphet()

metrics = m.fit(df, freq="D")

forecast = m.predict(df)

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