Machine Learning in Production
Completed by Angel Diaz Carral
June 9, 2024
11 hours (approximately)
Angel Diaz Carral'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: Application Deployment
- Category: Data Collection
- Category: Model Optimization
- Category: Data Maintenance
- Category: Data Preprocessing
- Category: Machine Learning
- Category: Model Deployment
- Category: Data Validation
- Category: Model Evaluation
- Category: Data Integrity
- Category: MLOps (Machine Learning Operations)
