Time-series forecasting with DLinear#
These tutorials implement an end-to-end time-series application including:
Distributed data preprocessing and model training: Ingest and preprocess data at scale using Ray Data. Then, train a distributed DLinear model using Ray Train.
Model validation using offline inference: Evaluate the model using Ray Data offline batch inference.
Online model serving: Deploy the model as a scalable online service using Ray Serve.
Production deployment: Create production batch Jobs for offline workloads including data prep, training, batch prediction, and potentially online Services.
Acknowledgements#
This repository is based on the official DLinear
implementations:
And the original publication: