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Python: Deeper Insights into Machine Learning

You're reading from   Python: Deeper Insights into Machine Learning Deeper Insights into Machine Learning

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Product type Course
Published in Aug 2016
Publisher Packt
ISBN-13 9781787128576
Length 901 pages
Edition 1st Edition
Languages
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Authors (3):
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John Hearty John Hearty
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John Hearty
Sebastian Raschka Sebastian Raschka
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Sebastian Raschka
David Julian David Julian
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David Julian
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Toc

Table of Contents (6) Chapters Close

Preface 1. Module 1 2. Module 2 FREE CHAPTER 3. Module 3 A. Biblography
Index

Chapter 9. Additional Python Machine Learning Tools

Over the course of the eight preceding chapters, we have examined and applied a range of techniques that help us enrich and model data for many applications.

We approached the content in these chapters using a combination of Python libraries, particularly NumPy and Theano, while the other libraries were drawn upon as and when we needed to access specific algorithms. We did not spend a great deal of time discussing what other options existed in terms of tools, what the unique differentiators of these tools were, or why we might be interested.

The primary goal of this final chapter is to highlight some other key libraries and frameworks that are available to you to use. These tools streamline and simplify the process of creating and applying models. This chapter presents these tools, demonstrates their application, and provides extensive advice regarding Further reading.

A major contributor to succeed in solving data science challenges...

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