Machine Learning in Production
Completed by Fazliddin Naimov
October 2, 2022
11 hours (approximately)
Fazliddin Naimov'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 Deployment
- Category: Data Preprocessing
- Category: Data Validation
- Category: Continuous Monitoring
- Category: Machine Learning
- Category: Model Training
- Category: Data Synthesis
- Category: Application Deployment
- Category: MLOps (Machine Learning Operations)
- Category: Continuous Deployment
- Category: Applied Machine Learning
- Category: Model Optimization
