/TimeSeries-Seq2Seq-deepLSTMs-Keras

This project aims to give you an introduction to how Seq2Seq based encoder-decoder neural network architectures can be applied on time series data to make forecasts. The code is implemented in pyhton with Keras (Tensorflow backend).

Primary LanguageJupyter Notebook

TimeSeries-Seq2Seq-deepLSTMs-Keras

This project aims to give you an introduction to how Seq2Seq based encoder-decoder neural network architectures can be applied on time series data to make forecasts. The code is implemented in pyhton with Keras (Tensorflow backend).

For a high level understanding of the project, do read my blog post on medium.com.