Machine Learning in Production
Completed by Karolina Ohradzanska
January 2, 2024
11 hours (approximately)
Karolina Ohradzanska'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 Preprocessing
- Category: Data Integrity
- Category: Data Validation
- Category: MLOps (Machine Learning Operations)
- Category: Continuous Deployment
- Category: Model Training
- Category: Data Quality
- Category: Model Optimization
- Category: Data Synthesis
- Category: Model Deployment
- Category: Model Evaluation
- Category: Unstructured Data
