Multi-input Time Series RNN-LSTM on continuous data value in Tensorflow

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Descripción

I'm trying to build a Time Series RNN with LSTM, with multiple continuous inputs features and the one continuous output, there is opensource code available however I just need to change the code so the algorithm can read from my dataset IE a CSV file as input and then the output being a CSV file it writes to. Most available code has inputs and outputs however does not have a section to provide new inputs it asks to predict. Tensorflow code would be ideal, I really just want the code in a position where I can easily update the hyper-parameters, inputs, output and new inputs to estimated once trained. If Tensorflow is not possible, I'd consider other code.

Habilidades: Aprendizaje automático, Python

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ID de proyecto: #12151211

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statAnalysis

Your project is a perfect match for my skills. Are you in a major rush with this project or is delivery within one week fine for you. best regards, Joerg.

$149 AUD en 7 días
(3 comentarios)
3.7

2 los freelancers están ofertando un promedio de $186 para este trabajo.

$155 AUD en 3 días
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AdeelAslam4

Hi there! I have read what you exactly need, however I would like to ask you a few questions. I wouldn't call myself a master but I do work smart and do not rest until I get the job done. Please feel free to ping me an Más

$222 AUD en 3 días
(1 comentario)
2.1