Machine Learning in Production
Completed by René Jörg Knaebel
October 17, 2024
11 hours (approximately)
René Jörg Knaebel'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: Unstructured Data
- Category: Data Integrity
- Category: Data Quality
- Category: Data Validation
- Category: Model Deployment
- Category: Continuous Monitoring
- Category: Data Collection
- Category: Machine Learning
- Category: Model Optimization
- Category: Application Deployment
- Category: System Monitoring
- Category: Data Preprocessing
