What are the Components of MLOps?
Machine Learning Operations have a set amount of core components which they use in order to perform Machine Learning operations. Some of the components are:
- Data Mining/input – The necessary data is taken from a database or mined by Data Miners.
- Data Preprocessing – The data mined is preprocessed, that is having null/incompatible data removed, rearranging data and so on.
- Training the Model – The preprocessed data is split into train and test batches and then fed to the model, training it.
- Parameter Tuning – The trained model’s accuracy is determined by running it with the testing batch. With the feedback/accuracy, the model’s parameters are tuned even more for higher accuracy values.
- Model Deployment – After satisfactory accuracy has been achieved, the model is then deployed to the cloud and its actions are observed.
- Redefining the model parameters – After a set amount of time, the model is again retrained over and over in order to make it susceptible to the data trends.
MLOps: Everything You Need to Know
The demand for data-related roles has been on a constant rise in recent years. The percentage of people shifting to the data industry from different technical backgrounds is growing constantly. Data Science and Analytics jobs are the highly competitive job roles that most people dream of.
However, other areas in the data industry are less known. Such is Machine Learning Operations (MLOps). Read the article till the end to learn about What is MLOps and to whom it is for.