Machine Learning in Production
Completed by Chanabasagouda Patil
April 9, 2024
11 hours (approximately)
Chanabasagouda Patil'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: Feature Engineering
- Category: Data Pipelines
- Category: Model Deployment
- Category: Data Preprocessing
- Category: Continuous Monitoring
- Category: Debugging
- Category: MLOps (Machine Learning Operations)
- Category: Applied Machine Learning
- Category: Data Quality
- Category: Machine Learning
- Category: Data Validation
