- Data Validation
- Applied Machine Learning
- Data Preprocessing
- Feature Engineering
- Machine Learning
- Data Quality
- Continuous Monitoring
- Model Evaluation
- Continuous Deployment
- Model Deployment
- Debugging
- Cloud Deployment
Machine Learning in Production
Completed by Najla Hussain Alqahtani
August 30, 2021
11 hours (approximately)
Najla Hussain Alqahtani'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
