This course includes
Course Overview
The goal of this course is to provide you with a set of tools that can be used to build predictive model services for product teams. In this course, you’ll start by covering the different cloud environments and tools for building scalable data and model pipelines. You’ll then learn the different data sets and types of models that will be used heavily in everyday production. Throughout the course, you’ll have plenty of exercises and challenges to get you comfortable working with the diverse toolset. Lastly...
Course Content
Introduction to Building Scalable Model Pipelines
Models as Web Endpoints
Models as Serverless Functions
Containers for Reproducible Models
Workflow Tools for Model Pipelines
PySpark for Batch Pipelines
25 Lessons
Cloud Dataflow for Batch Modeling
8 Lessons
Streaming Model Workflows
10 Lessons
Course Conclusion
1 Lesson
Course Author
Trusted by 1.4 million developers working at companies
Anthony Walker
@_webarchitect_
Evan Dunbar
ML Engineer
Carlos Matias La Borde
Software Developer
Souvik Kundu
Front-end Developer
Vinay Krishnaiah
Software Developer
Eric Downs
Musician/Entrepeneur
Kenan Eyvazov
DevOps Engineer
Souvik Kundu
Front-end Developer
Eric Downs
Musician/Entrepeneur
Anthony Walker
@_webarchitect_
Evan Dunbar
ML Engineer
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