Кроки для для здобуття необхідних навичок для спеціальностей з напрямку AI & Data на платформі Google Cloud Skills Boost завдяки можливості надданій Google Ukraine.
Курс: Production Machine Learning Systems
 |
| Production Machine Learning Systems, Mar 23, 2024 |
Summary
This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.
This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.
- Module 1: Architecting Production ML Systems
- Module 2: Designing Adaptable ML Systems
- Module 3: Designing High-performance ML Systems
- Module 4: Hybrid ML Systems
Machine Learning Engineer Learning Path
A Machine Learning Engineer designs, builds, productionizes, optimizes, operates, and maintains ML systems.
Summary
A Machine Learning Engineer designs, builds, productionizes, optimizes, operates, and maintains ML systems. This learning path guides you through a curated collection of on-demand courses, labs, and skill badges that provide you with real-world, hands-on experience using Google Cloud technologies essential to the ML Engineer role. Once you complete the path, check out the Google Cloud Machine Learning Engineer certification to take the next steps in your professional journey.
 |
| Machine Learning Engineer Learning Path |
#MachineLearning #MachineLearningModels #MachineLearningPipeline
Немає коментарів:
Дописати коментар