Machine Learning in Production
Completed by Alexander Anisimov
September 1, 2022
11 hours (approximately)
Alexander Anisimov'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 Quality
- Category: System Monitoring
- Category: Model Deployment
- Category: Unstructured Data
- Category: Data Maintenance
- Category: Applied Machine Learning
- Category: Application Deployment
- Category: Model Optimization
- Category: Continuous Deployment
- Category: Model Training
- Category: Data Integrity
- Category: Continuous Monitoring
