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Deep Learning with TensorFlow and Keras – 3rd edition - Third Edition

You're reading from  Deep Learning with TensorFlow and Keras – 3rd edition - Third Edition

Product type Book
Published in Oct 2022
Publisher Packt
ISBN-13 9781803232911
Pages 698 pages
Edition 3rd Edition
Languages
Authors (3):
Amita Kapoor Amita Kapoor
Profile icon Amita Kapoor
Antonio Gulli Antonio Gulli
Profile icon Antonio Gulli
Sujit Pal Sujit Pal
Profile icon Sujit Pal
View More author details

Table of Contents (23) Chapters

Preface 1. Neural Network Foundations with TF 2. Regression and Classification 3. Convolutional Neural Networks 4. Word Embeddings 5. Recurrent Neural Networks 6. Transformers 7. Unsupervised Learning 8. Autoencoders 9. Generative Models 10. Self-Supervised Learning 11. Reinforcement Learning 12. Probabilistic TensorFlow 13. An Introduction to AutoML 14. The Math Behind Deep Learning 15. Tensor Processing Unit 16. Other Useful Deep Learning Libraries 17. Graph Neural Networks 18. Machine Learning Best Practices 19. TensorFlow 2 Ecosystem 20. Advanced Convolutional Neural Networks 21. Other Books You May Enjoy
22. Index

ONNX

Open Neural Network Exchange (ONNX) provides an open-source format for AI models. It supports both deep learning models and traditional machine learning models. It is a format designed to represent any type of model, and it achieves this by using an intermediate representation of the computational graph created by different frameworks. It supports PyTorch, TensorFlow, MATLAB, and many more deep learning frameworks. Thus, using ONNX, we can easily convert models from one framework to another. This helps in reducing the time from research to deployment. For example, you can use ONNX to convert a PyTorch model to ONNX.js form, which can then be directly deployed on the web.

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