Machine Learning in Production
Completed by Anova Fawzi Rahman
October 26, 2024
11 hours (approximately)
Anova Fawzi Rahman'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: Application Deployment
- Category: Machine Learning
- Category: Model Optimization
- Category: System Monitoring
- Category: Data Synthesis
- Category: Continuous Deployment
- Category: MLOps (Machine Learning Operations)
- Category: Data Preprocessing
- Category: Data Maintenance
- Category: Data Validation
- Category: Applied Machine Learning
- Category: Model Evaluation
