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The Machine Learning Workshop

You're reading from   The Machine Learning Workshop Get ready to develop your own high-performance machine learning algorithms with scikit-learn

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839219061
Length 286 pages
Edition 2nd Edition
Languages
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Author (1):
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Hyatt Saleh Hyatt Saleh
Author Profile Icon Hyatt Saleh
Hyatt Saleh
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Introduction

In the previous chapters, we covered the main concepts of machine learning, beginning with the distinction between the two main learning approaches (supervised and unsupervised learning), and then moved on to the specifics of some of the most popular algorithms in the data science community.

This chapter will talk about the importance of building complete machine learning programs, rather than just training models. This will involve taking the models to the next level, where they can be accessed and used easily.

We will do this by learning how to save a trained model. This will allow the best performing model to be loaded in order to make predictions over unseen data. We will also learn the importance of making a saved model available through platforms where users can easily interact with it.

This is especially important when working in a team, either for a company or for research purposes, as it allows all members of the team to use the model without needing...

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