kaelzhang/DA-RNN-in-Tensorflow-2-and-PyTorch
A Tensorflow 2 (Keras) implementation of DA-RNN (A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction, arXiv:1704.02971)
This project helps data scientists and machine learning engineers build models that predict future values in time series data. It takes in historical time series measurements (like stock prices, sensor readings, or sales figures) and outputs a prediction for what those values will be at a future point. It's designed for practitioners who need to implement advanced attention-based recurrent neural networks in their prediction workflows.
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Use this if you are a data scientist or machine learning engineer looking to implement a sophisticated attention-based recurrent neural network (DA-RNN) for time series forecasting using either TensorFlow 2 or PyTorch.
Not ideal if you are an end-user without a programming background, as this is a developer tool requiring Python knowledge to use.
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May 02, 2024
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