Machine Learning in Production
Completed by Philip William Rolph
March 17, 2024
11 hours (approximately)
Philip William Rolph'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 Validation
- Category: Applied Machine Learning
- Category: Data Synthesis
- Category: Data Preprocessing
- Category: Data Collection
- Category: Application Deployment
- Category: Model Evaluation
- Category: Model Deployment
- Category: Data Quality
- Category: Model Training
- Category: Unstructured Data
- Category: Data Integrity
