Machine Learning in Production
Completed by Fatih Cakir
June 2, 2023
11 hours (approximately)
Fatih Cakir'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: Model Evaluation
- Category: Machine Learning
- Category: Cloud Deployment
- Category: Continuous Monitoring
- Category: MLOps (Machine Learning Operations)
- Category: Data Validation
- Category: Data Pipelines
- Category: Model Deployment
- Category: Applied Machine Learning
- Category: Continuous Deployment
- Category: Debugging
- Category: Data Preprocessing
