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Deep Learning Quick Reference

You're reading from  Deep Learning Quick Reference

Product type Book
Published in Mar 2018
Publisher Packt
ISBN-13 9781788837996
Pages 272 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Mike Bernico Mike Bernico
Profile icon Mike Bernico
LinkedIn
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.
See other products by Mike Bernico

Table of Contents (15) Chapters

Preface 1. The Building Blocks of Deep Learning 2. Using Deep Learning to Solve Regression Problems 3. Monitoring Network Training Using TensorBoard 4. Using Deep Learning to Solve Binary Classification Problems 5. Using Keras to Solve Multiclass Classification Problems 6. Hyperparameter Optimization 7. Training a CNN from Scratch 8. Transfer Learning with Pretrained CNNs 9. Training an RNN from scratch 10. Training LSTMs with Word Embeddings from Scratch 11. Training Seq2Seq Models 12. Using Deep Reinforcement Learning 13. Generative Adversarial Networks 14. Other Books You May Enjoy

Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

TensorFlow 1.x Deep Learning Cookbook
Antonio Gulli, Amita Kapoor

ISBN: 978-1-78829-359-4

  • Install TensorFlow and use it for CPU and GPU operations
  • Implement DNNs and apply them to solve different AI-driven problems.
  • Leverage different data sets such as MNIST, CIFAR-10, and Youtube8m with TensorFlow and learn how to access and use them in your code.
  • Use TensorBoard to understand neural network architectures, optimize the learning process, and peek inside the neural network black box.
  • Use different regression techniques for prediction and classification problems
  • Build single and multilayer perceptrons in TensorFlow

Deep Learning with Keras
Antonio Gulli, Sujit Pal

ISBN: 978-1-78712-842-2

  • Optimize step-by-step functions on a large neural network using the Backpropagation...
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Authors (1)

Profile icon Mike Bernico
LinkedIn
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.
See other products by Mike Bernico

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