LSTM forecasting on multivariate time series












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I'm new to RNNs and LSTM and would like some direction with a problem I have. I have a data set containing system metrics (like CPU utilization, disk operations, memory use) of an AWS EC2 instance with a total of 12 columns and around 10000 rows. Each row also has a timestamp with a 5 min interval between each row.



I want to build a LSTM model to forecast the performance for let's say the next hour based on my data. What would be the best approach for solving a problem like this? I know this can be done in many different ways but I would really appreciate some input how to go about this.









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    $begingroup$


    I'm new to RNNs and LSTM and would like some direction with a problem I have. I have a data set containing system metrics (like CPU utilization, disk operations, memory use) of an AWS EC2 instance with a total of 12 columns and around 10000 rows. Each row also has a timestamp with a 5 min interval between each row.



    I want to build a LSTM model to forecast the performance for let's say the next hour based on my data. What would be the best approach for solving a problem like this? I know this can be done in many different ways but I would really appreciate some input how to go about this.









    share







    New contributor




    Andreas is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







    $endgroup$















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      $begingroup$


      I'm new to RNNs and LSTM and would like some direction with a problem I have. I have a data set containing system metrics (like CPU utilization, disk operations, memory use) of an AWS EC2 instance with a total of 12 columns and around 10000 rows. Each row also has a timestamp with a 5 min interval between each row.



      I want to build a LSTM model to forecast the performance for let's say the next hour based on my data. What would be the best approach for solving a problem like this? I know this can be done in many different ways but I would really appreciate some input how to go about this.









      share







      New contributor




      Andreas is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I'm new to RNNs and LSTM and would like some direction with a problem I have. I have a data set containing system metrics (like CPU utilization, disk operations, memory use) of an AWS EC2 instance with a total of 12 columns and around 10000 rows. Each row also has a timestamp with a 5 min interval between each row.



      I want to build a LSTM model to forecast the performance for let's say the next hour based on my data. What would be the best approach for solving a problem like this? I know this can be done in many different ways but I would really appreciate some input how to go about this.







      machine-learning deep-learning lstm rnn





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      asked 3 mins ago









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