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.
machine-learning deep-learning lstm rnn
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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.
machine-learning deep-learning lstm rnn
New contributor
$endgroup$
add a comment |
$begingroup$
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.
machine-learning deep-learning lstm rnn
New contributor
$endgroup$
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
machine-learning deep-learning lstm rnn
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asked 3 mins ago
AndreasAndreas
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Andreas is a new contributor. Be nice, and check out our Code of Conduct.
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