Machine Learning in Production
Completed by Ana Carolina Nepomuceno Costa
May 18, 2022
11 hours (approximately)
Ana Carolina Nepomuceno Costa'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 Synthesis
- Category: Model Training
- Category: Data Integrity
- Category: Unstructured Data
- Category: Data Quality
- Category: Continuous Monitoring
- Category: Continuous Deployment
- Category: MLOps (Machine Learning Operations)
- Category: Applied Machine Learning
- Category: Model Evaluation
- Category: Data Collection
- Category: Data Validation
