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Deep Learning By Example

You're reading from   Deep Learning By Example A hands-on guide to implementing advanced machine learning algorithms and neural networks

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788399906
Length 450 pages
Edition 1st Edition
Languages
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Author (1):
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 Menshawy Menshawy
Author Profile Icon Menshawy
Menshawy
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Toc

Table of Contents (23) Chapters Close

Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
1. Data Science - A Birds' Eye View FREE CHAPTER 2. Data Modeling in Action - The Titanic Example 3. Feature Engineering and Model Complexity – The Titanic Example Revisited 4. Get Up and Running with TensorFlow 5. TensorFlow in Action - Some Basic Examples 6. Deep Feed-forward Neural Networks - Implementing Digit Classification 7. Introduction to Convolutional Neural Networks 8. Object Detection – CIFAR-10 Example 9. Object Detection – Transfer Learning with CNNs 10. Recurrent-Type Neural Networks - Language Modeling 11. Representation Learning - Implementing Word Embeddings 12. Neural Sentiment Analysis 13. Autoencoders – Feature Extraction and Denoising 14. Generative Adversarial Networks 15. Face Generation and Handling Missing Labels 16. Implementing Fish Recognition 1. Other Books You May Enjoy Index

Appendix 1. Other Books You May Enjoy

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

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 Algorithm
  • Fine-tune a neural network to improve the quality of results
  • Use deep learning for image and audio processing
  • Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases
  • Identify problems for which Recurrent Neural Network (RNN) solutions are suitable
  • Explore the process required to implement Autoencoders
  • Evolve a deep neural network using reinforcement learning

Deep Learning with TensorFlowGiancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy

ISBN: 978-1-78646-978-6

  • Learn about machine learning landscapes along with the historical development and progress of deep learning
  • Learn about deep machine intelligence and GPU computing with the latest TensorFlow 1.x
  • Access public datasets and utilize them using TensorFlow to load, process, and transform data
  • Use TensorFlow on real-world datasets, including images, text, and more
  • Learn how to evaluate the performance of your deep learning models
  • Using deep learning for scalable object detection and mobile computing
  • Train machines quickly to learn from data by exploring reinforcement learning techniques
  • Explore active areas of deep learning research and applications
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