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You're reading from  Deep Learning Quick Reference

Product typeBook
Published inMar 2018
Reading LevelExpert
PublisherPackt
ISBN-139781788837996
Edition1st Edition
Languages
Python
Tools
KerasTensorFlow
Concepts
Deep Learning
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Author (1)
Mike Bernico
Mike Bernico
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Mike Bernico

Mike Bernico is a Lead Data Scientist at State Farm Mutual Insurance Companies. He also works as an adjunct for the University of Illinois at Springfield, where he teaches Essentials of Data Science, and Advanced Neural Networks and Deep Learning. Mike earned his MSCS from the University of Illinois at Springfield. He's an advocate for open source software and the good it can bring to the world. As a lifelong learner with umpteen hobbies, Mike also enjoys cycling, travel photography, and wine making.
Read more about Mike Bernico

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Summary

Hyperparameter optimization is an important step in getting the very best from our deep neural networks. Finding the best way to search for hyperparameters is an open and active area of machine learning research. While you most certainly can apply the state of the art to your own deep learning problem, you will need to weigh the complexity of implementation against the search runtime in your decision.

There are decisions related to network architecture that most certainly can be searched exhaustively, but a set of heuristics and best practices, as I offered above, might get you close enough or even reduce the number of parameters you search.

Ultimately, hyperparameter search is an economics problem, and the first part of any hyperparameter search should be consideration for your budget of computation time, and personal time, in attempting to isolate the best hyperparameter...

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Deep Learning Quick Reference
Published in: Mar 2018Publisher: PacktISBN-13: 9781788837996
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Mike Bernico

Mike Bernico is a Lead Data Scientist at State Farm Mutual Insurance Companies. He also works as an adjunct for the University of Illinois at Springfield, where he teaches Essentials of Data Science, and Advanced Neural Networks and Deep Learning. Mike earned his MSCS from the University of Illinois at Springfield. He's an advocate for open source software and the good it can bring to the world. As a lifelong learner with umpteen hobbies, Mike also enjoys cycling, travel photography, and wine making.
Read more about Mike Bernico

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