Machine Learning in Production
Completed by Xiaoshuang Yin
May 23, 2024
11 hours (approximately)
Xiaoshuang Yin'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: Continuous Deployment
- Category: Machine Learning
- Category: Model Deployment
- Category: Data Collection
- Category: Data Synthesis
- Category: Data Preprocessing
- Category: Continuous Monitoring
- Category: System Monitoring
- Category: Application Deployment
- Category: Data Validation
- Category: Model Training
- Category: Data Integrity
