Machine Learning in Production
Completed by Enrique S. Ramirez
April 30, 2024
11 hours (approximately)
Enrique S. 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: Data Validation
- Category: Data Synthesis
- Category: Applied Machine Learning
- Category: Model Evaluation
- Category: Data Preprocessing
- Category: Data Collection
- Category: Continuous Deployment
- Category: Application Deployment
- Category: Data Maintenance
- Category: Unstructured Data
- Category: Data Integrity
- Category: Machine Learning
