It is difficult for data scientists to categorize data and construct correct machine learning models, but managing models in production might be even more difficult. Recognizing system drift, updating models with updated data sets, enhancing performance, and managing underlying technology platforms are all critical data science processes.
Click here to read more -->THE RISE OF MACHINE LEARNING OPERATIONS
