Reader small image

You're reading from  Python Machine Learning

Product typeBook
Published inSep 2015
Reading LevelIntermediate
PublisherPackt
ISBN-139781783555130
Edition1st Edition
Languages
Right arrow
Author (1)
Sebastian Raschka
Sebastian Raschka
author image
Sebastian Raschka

Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.
Read more about Sebastian Raschka

Right arrow

Summary


In this chapter, you learned about many useful and practical topics that extend our knowledge of machine learning theory. You learned how to serialize a model after training and how to load it for later use cases. Furthermore, we created a SQLite database for efficient data storage and created a web application that lets us make our movie classifier available to the outside world.

Throughout this book, we have really discussed a lot about machine learning concepts, best practices, and supervised models for classification. In the next chapter, we will take a look at another subcategory of supervised learning, regression analysis, which lets us predict outcome variables on a continuous scale, in contrast to the categorical class labels of the classification models that we have been working with so far.

lock icon
The rest of the page is locked
Previous PageNext Chapter
You have been reading a chapter from
Python Machine Learning
Published in: Sep 2015Publisher: PacktISBN-13: 9781783555130

Author (1)

author image
Sebastian Raschka

Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.
Read more about Sebastian Raschka