Machine Learning in Production
Completed by SIDI MOHAMED HICHAM ZEKRI
November 13, 2022
11 hours (approximately)
SIDI MOHAMED HICHAM ZEKRI'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 Pipelines
- Category: Continuous Deployment
- Category: Continuous Monitoring
- Category: Cloud Deployment
- Category: Applied Machine Learning
- Category: Debugging
- Category: Data Validation
- Category: Feature Engineering
- Category: Model Deployment
- Category: Data Quality
- Category: Model Evaluation
- Category: MLOps (Machine Learning Operations)
