Machine Learning in Production
Completed by TUNG HAN CHANG
June 30, 2024
11 hours (approximately)
TUNG HAN CHANG'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: Application Deployment
- Category: Continuous Monitoring
- Category: Applied Machine Learning
- Category: Data Validation
- Category: Model Optimization
- Category: System Monitoring
- Category: Machine Learning
- Category: Data Collection
- Category: Model Training
- Category: Model Evaluation
- Category: Continuous Deployment
- Category: MLOps (Machine Learning Operations)
