Machine Learning in Production
Completed by Aya ISSOUANI
March 13, 2024
11 hours (approximately)
Aya ISSOUANI'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: Model Optimization
- Category: System Monitoring
- Category: Machine Learning
- Category: Model Deployment
- Category: Applied Machine Learning
- Category: Continuous Monitoring
- Category: Model Evaluation
- Category: Data Collection
- Category: Data Validation
- Category: Application Deployment
- Category: Data Quality
- Category: Continuous Deployment
