Machine Learning in Production
Completed by Andreas Urech
January 10, 2022
11 hours (approximately)
Andreas Urech's account is verified. Coursera certifies their successful completion of Machine Learning in Production
What you will learn
Identify key components of the ML project lifecycle, pipeline & select the best deployment & monitoring patterns for different production scenarios.
Optimize model performance and metrics by prioritizing disproportionately important examples that represent key slices of a dataset.
Solve production challenges regarding structured, unstructured, small, and big data, how label consistency is essential, and how you can improve it.
Skills you will gain
- Category: Data Integrity
- Category: Continuous Monitoring
- Category: Model Deployment
- Category: Machine Learning
- Category: MLOps (Machine Learning Operations)
- Category: Model Evaluation
- Category: Model Training
- Category: Applied Machine Learning
- Category: Data Preprocessing
- Category: Model Optimization
- Category: Data Maintenance
- Category: Application Deployment
