Machine Learning in Production
Completed by Nir Kigelman
December 30, 2021
11 hours (approximately)
Nir Kigelman'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: Applied Machine Learning
- Category: Continuous Monitoring
- Category: Data Preprocessing
- Category: Data Maintenance
- Category: Application Deployment
- Category: Data Integrity
- Category: Model Evaluation
- Category: Model Optimization
- Category: Continuous Deployment
- Category: Data Quality
- Category: Data Collection
- Category: MLOps (Machine Learning Operations)
