Machine Learning in Production
Completed by emile salem
June 21, 2021
11 hours (approximately)
emile salem'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: System Monitoring
- Category: Data Integrity
- Category: Machine Learning
- Category: MLOps (Machine Learning Operations)
- Category: Model Optimization
- Category: Continuous Deployment
- Category: Data Synthesis
- Category: Unstructured Data
- Category: Data Preprocessing
- Category: Model Training
- Category: Data Validation
- Category: Application Deployment
