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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.
| Date | Stars |
|---|---|
| 2026-07-31 | 613 |
| 2026-08-02 | 613 |
| 2026-08-05 | 613 |
| 2026-08-06 | 613 |
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# TimeSeries_Seq2Seq This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow. ## Instructions for Working With Notebooks: Navigate to the directory you want the git repo to live in. 1. Run ```git clone https://github.com/JEddy92/TimeSeries_Seq2Seq.git``` 2. Obtain the wikipedia web traffic data from [kaggle](https://www.kaggle.com/c/web-traffic-time-series-forecasting/data). Store it in a folder called "data" at the top level of this repo (this is where the notebooks point to when reading data).
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matched fp:f5dcae6f88ccf1a3, llm:Repository description: 'collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.'
matched fp:f5dcae6f88ccf1a3, llm:Repository description: 'collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.'
matched fp:f5dcae6f88ccf1a3, llm:Repository description: 'collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.'