Machine Learning in Production
Completed by Neha Dave
May 20, 2021
11 hours (approximately)
Neha Dave'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 Validation
- Category: Continuous Deployment
- Category: Model Evaluation
- Category: Data Collection
- Category: Data Preprocessing
- Category: Continuous Monitoring
- Category: Application Deployment
- Category: Model Optimization
- Category: System Monitoring
- Category: Machine Learning
- Category: Data Quality
