Machine Learning in Production
Completed by Pieter Vierstraete
June 6, 2022
11 hours (approximately)
Pieter Vierstraete'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: Model Deployment
- Category: Continuous Monitoring
- Category: Data Maintenance
- Category: Application Deployment
- Category: Model Evaluation
- Category: Unstructured Data
- Category: Data Integrity
- Category: Model Training
- Category: Data Quality
- Category: Continuous Deployment
- Category: MLOps (Machine Learning Operations)
- Category: Model Optimization
