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Python: Real World Machine Learning
book

Python: Real World Machine Learning

by Prateek Joshi, John Hearty, Bastiaan Sjardin, Luca Massaron, Alberto Boschetti
November 2016
Beginner to intermediate
941 pages
21h 55m
English
Packt Publishing
Content preview from Python: Real World Machine Learning

Summary

In this chapter, we expanded on the initial discussion of out-of-core algorithms by adding SVMs to simple regression-based linear models. Most of the time, we focused on Scikit-learn implementations—mostly SGD—and concluded with an overview of external tools that can be integrated with Python scripts, such as Vowpal Wabbit by John Langford. Along the way, we completed our overview on model improvement and validation technicalities when working out-of-core by discussing reservoir sampling, regularization, explicit and implicit nonlinear transformations, and hyperparameter optimization.

In the next chapter, we will get involved with even more complex and powerful learning approaches while presenting deep learning and neural networks in large ...

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Publisher Resources

ISBN: 9781787123212Supplemental ContentPurchase Link