Machine Learning in Production
Completed by Ryan Shnitman
July 13, 2021
11 hours (approximately)
Ryan Shnitman'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: MLOps (Machine Learning Operations)
- Category: Data Maintenance
- Category: Model Optimization
- Category: Model Deployment
- Category: Data Preprocessing
- Category: Model Evaluation
- Category: Unstructured Data
- Category: Model Training
- Category: Data Validation
- Category: Machine Learning
- Category: Applied Machine Learning
- Category: Continuous Monitoring
