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Generative AI with Python and TensorFlow 2

You're reading from  Generative AI with Python and TensorFlow 2

Product type Book
Published in Apr 2021
Publisher Packt
ISBN-13 9781800200883
Pages 488 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
Joseph Babcock Joseph Babcock
Profile icon Joseph Babcock
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Raghav Bali Raghav Bali
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Table of Contents (16) Chapters

Preface 1. An Introduction to Generative AI: "Drawing" Data from Models 2. Setting Up a TensorFlow Lab 3. Building Blocks of Deep Neural Networks 4. Teaching Networks to Generate Digits 5. Painting Pictures with Neural Networks Using VAEs 6. Image Generation with GANs 7. Style Transfer with GANs 8. Deepfakes with GANs 9. The Rise of Methods for Text Generation 10. NLP 2.0: Using Transformers to Generate Text 11. Composing Music with Generative Models 12. Play Video Games with Generative AI: GAIL 13. Emerging Applications in Generative AI 14. Other Books You May Enjoy
15. Index

References

  1. Eckersley P., Nasser Y. Measuring the Progress of AI Research. EFF. Retrieved April 26, 2021, https://www.eff.org/ai/metrics#Measuring-the-Progress-of-AI-Research and CIFAR-10 datasets, https://www.cs.toronto.edu/~kriz/
  2. Malhotra P. (2018). Autoencoder-Implementations. GitHub repository. https://www.piyushmalhotra.in/Autoencoder-Implementations/VAE/
  3. Kingma, D P., Welling, M. (2014). Auto-Encoding Variational Bayes. arXiv:1312.6114. https://arxiv.org/pdf/1312.6114.pdf
  4. Hinton G. E., Salakhutdinov R. R. (2006). Reducing the Dimensionality of Data with Neural Networks. ScienceMag. https://www.cs.toronto.edu/~hinton/science.pdf
  5. Hinton G. E., Salakhutdinov R. R. (2006). Reducing the Dimensionality of Data with Neural Networks. ScienceMag. https://www.cs.toronto.edu/~hinton/science.pdf
  6. Kingma, D P., Welling, M. (2014). Auto-Encoding Variational Bayes. arXiv:1312.6114. https://arxiv.org/pdf/1312.6114.pdf
  7. Doersch, C. (2016). Tutorial on...
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Authors (2)

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Profile icon Joseph Babcock
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Profile icon Raghav Bali
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