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Table Of Contents
Machine Learning in Microservices
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In this chapter, we looked at the different key components that make up a machine learning pipeline.
From there, we looked in detail at the interfaces that make up the components. We started with the transform interface, which is responsible for the data aspect of the pipeline. It takes the data and applies different types of data transformation that allow us to maintain clean and stable data, which we can later use in our machine learning model.
After our transformation stage, we start creating our model in the fit interface. Here, we can use the prebuilt models that the libraries and packages offer to initialize our models. Due to the ease of creating models, it is a good practice to test different types of models to see which model performs the best based on our data.
Once we have created our model, we can begin the actual training of our model. We need to split our data into training and test sets to allow our model to understand the relationship in our data. From...
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