Machine Learning in Production
Completed by Sydney Schramm
November 15, 2024
11 hours (approximately)
Sydney Schramm'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 Preprocessing
- Category: Data Quality
- Category: Data Integrity
- Category: Unstructured Data
- Category: MLOps (Machine Learning Operations)
- Category: Continuous Deployment
- Category: Data Maintenance
- Category: Data Validation
- Category: Model Optimization
- Category: System Monitoring
- Category: Machine Learning
- Category: Data Synthesis
