课程: AutoML: Build Production-Ready Models Quickly!
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AutoML tools: Why use them? - Python教程
课程: AutoML: Build Production-Ready Models Quickly!
AutoML tools: Why use them?
- [Narrator] So far, we have looked at simplified examples of the machine learning process using insurance data. Even in our simplified scenario, there were a number of considerations to be made about how data is cleaned, prepared, and visualized. We also dealt with modeling decisions. What model best fits our problem, and how to train this model to meet business objectives by evaluating it properly and tuning its hyperparameters. The last thing we looked at is preparing the trained model to be used in production to make predictions on new data. This involved saving the model in a shareable format as well as saving its hyperparameters. So it is clear that the machine learning process is an iterative one. Many of its steps can also be very manual and repetitive. Thankfully there are tools that can help us abstract away some of these steps. They are called AutoML tools, and they give us a number of advantages as data…
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