NBEATS · PyPI
https://pypi.org/project/NBEATS03.01.2011 · forecast_length; Basic model with only mandatory parameters can be used to get forecasted values as shown below: import pandas as pd from NBEATS import NeuralBeats data = pd.read_csv ('test.csv') data = data.values # (nx1 array) model = NeuralBeats (data = data, forecast_length = 5) model.fit forecast = model.predict Optional parameters to the ...
pytorch-forecasting · PyPI
pypi.org › project › pytorch-forecastingNov 29, 2021 · PyTorch Forecasting is a PyTorch-based package for forecasting time series with state-of-the-art network architectures. It provides a high-level API for training networks on pandas data frames and leverages PyTorch Lightning for scalable training on (multiple) GPUs, CPUs and for automatic logging. Our article on Towards Data Science introduces ...
nbeats-pytorch · PyPI
https://pypi.org/project/nbeats-pytorch04.08.2021 · Example. Jupyter notebook: NBeats.ipynb: make run-jupyter. Here is a toy example on how to use this model (train/inference) for the Keras and Pytorch backends. Note that only the Keras backend supports input_dim>1 (at the moment). import warnings import numpy as np from nbeats_keras.model import NBeatsNet as NBeatsKeras from nbeats_pytorch ...