What are the key stages in an MLOps pipeline?

An MLOps pipeline typically comprises several key stages: 1. Data Collection: Gathering data from various sources. 2. Data Preprocessing: Cleaning and transforming the data for analysis. 3. Model Training: Using algorithms to learn patterns from the training data. 4. Model Evaluation: Assessing the model's performance using validation datasets. 5. Deployment: Making the model available for predictions in a production environment. 6. Monitoring: Tracking model performance and data quality in real-time. 7. Retraining: Updating the model with new data to maintain accuracy.