Tuning LSTM RNN prediction model hyperparameters
Budget: $30 – $250 USD
I am looking for a freelancer to help me tune the hyperparameters of my LSTM RNN prediction model. The project involves working with a small dataset of less than 1000 data points and using Python as the preferred programming language.
The main purpose of tuning the hyperparameters is to improve the model accuracy.
Ideal skills and experience for this job include:
- Strong knowledge of LSTM RNN models and their hyperparameters
- Proficiency in Python and its machine learning libraries
- Experience in working with small datasets
- Understanding of model accuracy improvement techniques and strategies
If you have the expertise in LSTM RNN models and hyperparameter tuning, and are proficient in Python, I would love to discuss the project further with you.
Description of the project:
We have a LSTM RNN prediction model that predicts future CPU usage (next value). However comparing the performance of this model with naive forecast, we find that MSE of our model is higher than MSE of naive forecast. That means our model doesn’t perform well. For this reason, we need someone who knows about prediction models, RNN, and LSTM.
The requirements are the following:
Tune the RNN model to get better prediction than naive forecast.
Get train and test MSE
Get train and test RMSE
Test MSE of RNN model must be better (lower) than MSE of naive forecast model
Complete and clear documentation about how the tuning process was made
Deliver document guides about how the test was made.
Delivery all the documentation in a professional way.
Provide advice and training through Meet videocall.
The main purpose of tuning the hyperparameters is to improve the model accuracy.
Ideal skills and experience for this job include:
- Strong knowledge of LSTM RNN models and their hyperparameters
- Proficiency in Python and its machine learning libraries
- Experience in working with small datasets
- Understanding of model accuracy improvement techniques and strategies
If you have the expertise in LSTM RNN models and hyperparameter tuning, and are proficient in Python, I would love to discuss the project further with you.
Description of the project:
We have a LSTM RNN prediction model that predicts future CPU usage (next value). However comparing the performance of this model with naive forecast, we find that MSE of our model is higher than MSE of naive forecast. That means our model doesn’t perform well. For this reason, we need someone who knows about prediction models, RNN, and LSTM.
The requirements are the following:
Tune the RNN model to get better prediction than naive forecast.
Get train and test MSE
Get train and test RMSE
Test MSE of RNN model must be better (lower) than MSE of naive forecast model
Complete and clear documentation about how the tuning process was made
Deliver document guides about how the test was made.
Delivery all the documentation in a professional way.
Provide advice and training through Meet videocall.