MPG.eBooks - Table of Contents: State-of-the-art deep learning models in Tensorflow

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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...

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Bibliographic Details
Main Author:	Paper, David
Format:	eBook
Language:	English
Published:	[United States] Apress 2021
Subjects:	Machine Learning / Fast Apprentissage Automatique Machine Learning / Http://id.loc.gov/authorities/subjects/sh85079324 Reinforcement Learning / Fast Apprentissage Par Renforcement (intelligence Artificielle) Reinforcement Learning / Http://id.loc.gov/authorities/subjects/sh92000704 Tensorflow / Http://id.loc.gov/authorities/names/n2019020612
Online Access:	https://learning.oreilly.com/library/view/~/978148...
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

State-of-the-art deep learning models in Tensorflow modern machine learning in the Google colab ecosystem

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