Machine Learning in Production
Completed by Jorge Castro
April 2, 2022
11 hours (approximately)
Jorge Castro'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 Deployment
- Category: Data Maintenance
- Category: MLOps (Machine Learning Operations)
- Category: Model Optimization
- Category: System Monitoring
- Category: Machine Learning
- Category: Continuous Monitoring
- Category: Application Deployment
- Category: Data Quality
- Category: Model Deployment
- Category: Model Evaluation
- Category: Data Collection
