Machine Learning in Production
Completed by Yevhenii Yavorski
April 14, 2024
11 hours (approximately)
Yevhenii Yavorski'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 Quality
- Category: Model Training
- Category: Applied Machine Learning
- Category: Data Integrity
- Category: Machine Learning
- Category: Model Optimization
- Category: System Monitoring
- Category: Data Synthesis
- Category: Data Validation
- Category: Data Preprocessing
- Category: Continuous Deployment
- Category: MLOps (Machine Learning Operations)
