Machine Learning in Production
Completed by Danielle Heymann
October 9, 2022
11 hours (approximately)
Danielle Heymann'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: Continuous Monitoring
- Category: Data Quality
- Category: Data Maintenance
- Category: MLOps (Machine Learning Operations)
- Category: Model Deployment
- Category: Machine Learning
- Category: System Monitoring
- Category: Model Training
- Category: Unstructured Data
- Category: Data Integrity
- Category: Data Synthesis
- Category: Application Deployment
