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Applied Data Science with Python and Jupyter

You're reading from   Applied Data Science with Python and Jupyter Use powerful industry-standard tools to unlock new, actionable insights from your data

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Product type Paperback
Published in Oct 2018
Publisher
ISBN-13 9781789958171
Length 192 pages
Edition 1st Edition
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Author (1):
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Alex Galea Alex Galea
Author Profile Icon Alex Galea
Alex Galea
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Preparing to Train a Predictive Model


Here, we will cover the preparation required to train a predictive model. Although not as technically glamorous as training the models themselves, this step should not be taken lightly. It's very important to ensure you have a good plan before proceeding with the details of building and training a reliable model. Furthermore, once you've decided on the right plan, there are technical steps in preparing the data for modeling that should not be overlooked.

Note

We must be careful not to go so deep into the weeds of technical tasks that we lose sight of the goal. Technical tasks include things that require programming skills, for example, constructing visualizations, querying databases, and validating predictive models. It's easy to spend hours trying to implement a specific feature or get the plots looking just right. Doing this sort of thing is certainly beneficial to our programming skills, but we should not forget to ask ourselves if it's really worth...

You have been reading a chapter from
Applied Data Science with Python and Jupyter
Published in: Oct 2018
Publisher:
ISBN-13: 9781789958171
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