NHITS: A Complete Tutorial for Deep Learning Time-Series Forecasting
Learn how to use a high-performance DL forecasting model
Our previous article described the architecture of NHITS in detail and explained why it’s a powerful model.
NHITS shines by integrating signal processing concepts, making it both accurate and lightweight for a DL model.
In this follow-up article, we will use NHITS to build an end-to-end project on Energy Demand Forecasting. Specifically, we will cover:
Univariate Forecasting.
Integrating Future Known Covariates.
Visualizing Model Training Results with TensorBoard.
Hyperparameter Tuning with Ray and HyperOptSearch.
Let’s get started!
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NHITS Project
You can also find the full project on the AI Projects Folder.