State-of-the-art deep learning models in Tensorflow modern machine learning in the Google colab ecosystem
What You Will Learn Take advantage of the built-in support of the Google Colab ecosystem Work with TensorFlow data sets Create input pipelines to feed state-of-the-art deep learning models Create pipelined state-of-the-art deep learning models with clean and reliable Python code Leverage pre-trained...
Main Author: | |
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Format: | eBook |
Language: | English |
Published: |
[United States]
Apress
2021
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Online Access: | |
Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- 1. Build TensorFlow Input Pipelines
- 2. Increase the Diversity of your Dataset with Data Augmentation
- 3. TensorFlow Datasets
- 4. Deep Learning with TensorFlow Datasets
- 5. Introduction to Tensor Processing Units
- 6. Simple Transfer Learning with TensorFlow Hub
- 7. Advanced Transfer Learning
- 8. Stacked Autoencoders
- 9. Convolutional and Variational Autoencoders
- 10. Generative Adversarial Networks
- 11. Progressive Growing Generative Adversarial Networks
- 12. Fast Style Transfer
- 13. Object Detection
- 14. An Introduction to Reinforcement Learning