From the course: MLOps Essentials: Model Development and Integration
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Notebook to software
From the course: MLOps Essentials: Model Development and Integration
Notebook to software
- [Instructor] The notebook to software step deals with producing a deployable and executable version of the model. Code in ML notebooks need to be converted to executable software before it can be integrated and deployed. This conversion should ensure that processing and model aspects from the notebook are faithfully reproduced into the code, and has the same performance as the notebook. There are multiple ways in which a model can be made into an executable form. This depends upon the type of use case and deployment. To begin with, the model can be provided as embedded software, where it gets embedded into non-ML executables. Alternatively, it can be its own running service that receives requests from clients and returns responses. The use cases could be batch or historical predictions and streaming or online predictions. If it's an embedded software, it does not make a difference between the use cases. The model…
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