Machine Learning in Production
Completed by Afaque Ahmad
September 18, 2024
11 hours (approximately)
Afaque Ahmad'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 Quality
- Category: Unstructured Data
- Category: Data Integrity
- Category: Application Deployment
- Category: Model Optimization
- Category: System Monitoring
- Category: Machine Learning
- Category: MLOps (Machine Learning Operations)
- Category: Continuous Deployment
- Category: Data Maintenance
- Category: Applied Machine Learning
- Category: Data Synthesis
