Machine Learning in Production
Completed by Nathanael David Neece
August 29, 2024
11 hours (approximately)
Nathanael David Neece'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 Integrity
- Category: Data Quality
- Category: Model Training
- Category: Application Deployment
- Category: Unstructured Data
- Category: Data Preprocessing
- Category: Applied Machine Learning
- Category: Data Synthesis
- Category: Model Evaluation
- Category: Data Collection
- Category: Data Validation
- Category: Model Deployment
