Machine Learning in Production
Completed by Aish Venketeswaran
September 22, 2024
11 hours (approximately)
Aish Venketeswaran'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: Model Evaluation
- Category: Data Pipelines
- Category: Data Quality
- Category: Continuous Monitoring
- Category: Data Preprocessing
- Category: Applied Machine Learning
- Category: Cloud Deployment
- Category: Feature Engineering
- Category: Data Validation
- Category: Debugging
