MLOps (Machine Learning Operations) is a set of practices, processes, and tools that support the creation, deployment, and maintenance of artificial intelligence and machine learning models in a production environment.
MLOps combines the fields of data science, data engineering, and DevOps, enabling the automation of the entire AI model lifecycle – from data preparation and model training to monitoring their performance and updates.
The MLOps process typically involves:
- data preparation and integration,
- machine learning model training,
- model testing and validation,
- deployment automation,
- monitoring model quality and effectiveness,
- model updates based on new data.
Thanks to MLOps, organizations can deploy AI solutions faster, increase project scalability, and better control the quality of models used in business.