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PT27227
Training Summary
Machine Learning is all the rage today. Most ML courses focus on building models. However, taking the ML models to production involves quite a bit of extra work. This course will teach Machine Learning Engineering – the process of productionizing, monitoring, and managing ML models.
Prerequisites
Students for this course should possess the following:
- Basic knowledge of Machine Learning or Deep Learning
- Python basic programming recommended
Duration
3 Days/Lecture & Lab
Audience
This course is intended for Data Scientists, DevOps, and Data Engineers.
Course Topics
- Machine Learning Engineering Overview
- Cloud Storage
- Cloud Compute
- Training in the cloud with GPUs
- Creating a Model Service
- Containerizing the app
- Deploying the Container in the Cloud
- Load-testing the application
- A/B Testing of Models
- Updating your model
- Final Workshop (Time Permitting)