Machine Learning in Production
Completed by Misael Antonio Alarcón Herrera
May 27, 2024
11 hours (approximately)
Misael Antonio Alarcón Herrera'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: Continuous Deployment
- Category: MLOps (Machine Learning Operations)
- Category: Data Maintenance
- Category: Data Collection
- Category: Data Validation
- Category: Model Evaluation
- Category: Data Preprocessing
- Category: Data Synthesis
- Category: Applied Machine Learning
- Category: Application Deployment
- Category: Model Optimization
- Category: System Monitoring
