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You have developed a model to forecast daily temperatures. Initially, you randomly divided the data, followed by transforming both the training and test datasets. While the model was trained with hourly-updated temperature data and achieved 97% accuracy in testing, its accuracy plummeted to 66% post-deployment in production. What steps can you take to enhance the accuracy of your model in the production environment?