Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Deep Learning with TensorFlow 2 and Keras

You're reading from   Deep Learning with TensorFlow 2 and Keras Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API

Arrow left icon
Product type Paperback
Published in Dec 2019
Publisher Packt
ISBN-13 9781838823412
Length 646 pages
Edition 2nd Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Dr. Amita Kapoor Dr. Amita Kapoor
Author Profile Icon Dr. Amita Kapoor
Dr. Amita Kapoor
Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
Antonio Gulli Antonio Gulli
Author Profile Icon Antonio Gulli
Antonio Gulli
Arrow right icon
View More author details
Toc

Table of Contents (19) Chapters Close

Preface 1. Neural Network Foundations with TensorFlow 2.0 2. TensorFlow 1.x and 2.x FREE CHAPTER 3. Regression 4. Convolutional Neural Networks 5. Advanced Convolutional Neural Networks 6. Generative Adversarial Networks 7. Word Embeddings 8. Recurrent Neural Networks 9. Autoencoders 10. Unsupervised Learning 11. Reinforcement Learning 12. TensorFlow and Cloud 13. TensorFlow for Mobile and IoT and TensorFlow.js 14. An introduction to AutoML 15. The Math Behind Deep Learning 16. Tensor Processing Unit 17. Other Books You May Enjoy
18. Index

AutoKeras

AutoKeras [6] provides functions to automatically search for the architecture and hyperparameters of deep learning models. The framework uses Bayesian optimization for efficient neural architecture search. You can install the alpha version by using pip:

pip3 install autokeras # for 0.4 version
pip3 install git+git://github.com/keras-team/autokeras@master#egg=autokeras # for 1.0 version

The architecture is explained in Figure 3 (taken from [6]):

  1. The user calls the API
  2. The searcher generates neural architectures on CPU
  3. Real neural networks with parameters on RAM from the neural architectures
  4. The neural network is copied to GPU for training
  5. Trained neural networks are saved on storage devices
  6. The searcher is updated based on the training results

Steps 2 to 6 will repeat until a time limit is reached:

Figure 3: AutoKeras system overview

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime