Machine Learning Modeling Pipelines in Production
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Course overview
- Provider
- Coursera
- Course type
- Free online course
- Level
- Advanced
- Deadline
- Flexible
- Duration
- 26 hours
- Certificate
- Paid Certificate Available
- Course author
- Robert Crowe
-
Apply techniques to manage modeling resources and best serve batch and real-time inference requests.
Use analytics to address model fairness, explainability issues, and mitigate bottlenecks.
Description
In the third course of Machine Learning Engineering for Production Specialization, you will build models for different serving environments; implement tools and techniques to effectively manage your modeling resources and best serve offline and online inference requests; and use analytics tools and performance metrics to address model fairness, explainability issues, and mitigate bottlenecks.Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need production engineering capabilities as well. Machine learning engineering for production combines the foundational concepts of machine learning with the functional expertise of modern software development and engineering roles to help you develop production-ready skills.
Week 1: Neural Architecture Search
Week 2: Model Resource Management Techniques
Week 3: High-Performance Modeling
Week 4: Model Analysis
Week 5: Interpretability
