Catch prices and volumes are an important component of the data. However, many errors are introduced when enumerators record this information. We aim to solve that by using a model of price and weight. Using the model predictions we can then identify records that are unlikely to be correct or should be reviewed.
This model should be re-trained in a monthly basis. Depending on the model complexity and training time it can run on GitHub runners or cloud providers computing instances (e.g. Google Cloud Run or Amazon EC2/Batch).
Catch prices and volumes are an important component of the data. However, many errors are introduced when enumerators record this information. We aim to solve that by using a model of price and weight. Using the model predictions we can then identify records that are unlikely to be correct or should be reviewed.
This model should be re-trained in a monthly basis. Depending on the model complexity and training time it can run on GitHub runners or cloud providers computing instances (e.g. Google Cloud Run or Amazon EC2/Batch).