Hansika Hewamalage | DeepAI

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∙ 03/21/2022

Forecast Evaluation for Data Scientists: Common Pitfalls and Best Practices

Machine Learning (ML) and Deep Learning (DL) methods are increasingly re...

125 Hansika Hewamalage, et al. ∙

∙ 11/29/2021

NeuralProphet: Explainable Forecasting at Scale

We introduce NeuralProphet, a successor to Facebook Prophet, which set a...

0 Oskar Triebe, et al. ∙

∙ 08/08/2021

A Look at the Evaluation Setup of the M5 Forecasting Competition

Forecast evaluation plays a key role in how empirical evidence shapes th...

3 Hansika Hewamalage, et al. ∙

∙ 12/23/2020

Global Models for Time Series Forecasting: A Simulation Study

In the current context of Big Data, the nature of many forecasting probl...

0 Hansika Hewamalage, et al. ∙

∙ 08/06/2020

Improving the Accuracy of Global Forecasting Models using Time Series Data Augmentation

Forecasting models that are trained across sets of many time series, kno...

0 Kasun Bandara, et al. ∙

∙ 09/10/2019

LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series with Multiple Seasonal Patterns

Generating forecasts for time series with multiple seasonal cycles is an...

17 Kasun Bandara, et al. ∙

∙ 09/02/2019

Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions

Recurrent Neural Networks (RNN) have become competitive forecasting meth...

77 Hansika Hewamalage, et al. ∙

∙ 01/13/2019

Sales Demand Forecast in E-commerce using a Long Short-Term Memory Neural Network Methodology

Generating accurate and reliable sales forecasts is crucial in the E-com...

0 Kasun Bandara, et al. ∙

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