Machine Learning in Production
Completed by Nicholas Smith
January 25, 2024
11 hours (approximately)
Nicholas Smith'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 Evaluation
- Category: Data Collection
- Category: Data Validation
- Category: Model Deployment
- Category: Model Optimization
- Category: System Monitoring
- Category: MLOps (Machine Learning Operations)
- Category: Continuous Deployment
- Category: Data Maintenance
- Category: Model Training
- Category: Data Quality
- Category: Unstructured Data
