Machine Learning in Production
Completed by RYAN ANDREW DUNCAN
May 16, 2022
11 hours (approximately)
RYAN ANDREW DUNCAN'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 Validation
- Category: Model Optimization
- Category: System Monitoring
- Category: Machine Learning
- Category: Model Evaluation
- Category: Model Deployment
- Category: Data Collection
- Category: Unstructured Data
- Category: Data Integrity
- Category: Application Deployment
- Category: Data Quality
- Category: Continuous Deployment
