Machine Learning in Production
Completed by Nicolas Bravo
July 15, 2024
11 hours (approximately)
Nicolas Bravo'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: Data Preprocessing
- Category: Model Optimization
- Category: Continuous Monitoring
- Category: Applied Machine Learning
- Category: Model Training
- Category: Application Deployment
- Category: Data Synthesis
- Category: Data Validation
- Category: Data Maintenance
- Category: Data Quality
- Category: Model Deployment
- Category: MLOps (Machine Learning Operations)
