Machine Learning in Production
Completed by Carlos Roberto de Aguinaga Ramirez
December 18, 2024
11 hours (approximately)
Carlos Roberto de Aguinaga Ramirez'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: Machine Learning
- Category: System Monitoring
- Category: Application Deployment
- Category: Model Optimization
- Category: Data Quality
- Category: Unstructured Data
- Category: Data Integrity
- Category: Data Maintenance
- Category: Data Preprocessing
- Category: Applied Machine Learning
- Category: Model Training
- Category: Data Synthesis
