LSTM Model Optimization for Sea Level Prediction
Budget: $10 – $30 USD
I'm working on a Stacked LSTM model with data spanning from 1993-2022 to predict sea level anomalies at six locations for the next year. I have sea surface temperature and sea level pressure as features. I've completed the analysis for two locations, but I'm struggling to achieve a satisfactory R² score for the remaining four.
Key Requirements:
- A data preprocessing expert to advise and implement on handling missing values, feature selection, and potentially other preprocessing steps.
- A machine learning specialist with extensive experience in LSTM models, particularly Stacked LSTMs.
- An individual with proficient knowledge in hyperparameter tuning who can help improve model performance beyond my current manual attempts.
- An expert in data augmentation techniques to help expand the dataset and potentially improve model performance.
- A specialist in time series modeling who can provide insights and methodologies specific to sequential data analysis.
- A specialist with experience in developing and implementing custom loss functions that could be more suitable for the sea level prediction task.
- An expert in model validation techniques to ensure that the model is not overfitting and has good generalization capabilities.
- A professional knowledgeable in advanced feature engineering to create new features from existing data that may improve predictions.
I have already normalized and standardized the data. Please provide your insights and suggestions to help enhance the model's predictive capability for the remaining four locations.
Key Requirements:
- A data preprocessing expert to advise and implement on handling missing values, feature selection, and potentially other preprocessing steps.
- A machine learning specialist with extensive experience in LSTM models, particularly Stacked LSTMs.
- An individual with proficient knowledge in hyperparameter tuning who can help improve model performance beyond my current manual attempts.
- An expert in data augmentation techniques to help expand the dataset and potentially improve model performance.
- A specialist in time series modeling who can provide insights and methodologies specific to sequential data analysis.
- A specialist with experience in developing and implementing custom loss functions that could be more suitable for the sea level prediction task.
- An expert in model validation techniques to ensure that the model is not overfitting and has good generalization capabilities.
- A professional knowledgeable in advanced feature engineering to create new features from existing data that may improve predictions.
I have already normalized and standardized the data. Please provide your insights and suggestions to help enhance the model's predictive capability for the remaining four locations.