Machine Learning in Production
Completed by Simone Faricelli
December 3, 2021
11 hours (approximately)
Simone Faricelli'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 Validation
- Category: Data Maintenance
- Category: Data Synthesis
- Category: Model Optimization
- Category: Unstructured Data
- Category: Data Integrity
- Category: Model Training
- Category: Data Preprocessing
- Category: System Monitoring
- Category: Continuous Monitoring
- Category: Model Deployment
- Category: Data Quality
