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TensorFlow Deep Learning Projects

You're reading from   TensorFlow Deep Learning Projects 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788398060
Length 320 pages
Edition 1st Edition
Languages
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Authors (5):
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Alberto Boschetti Alberto Boschetti
Author Profile Icon Alberto Boschetti
Alberto Boschetti
Rajalingappaa Shanmugamani Rajalingappaa Shanmugamani
Author Profile Icon Rajalingappaa Shanmugamani
Rajalingappaa Shanmugamani
Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Abhishek Thakur Abhishek Thakur
Author Profile Icon Abhishek Thakur
Abhishek Thakur
Alexey Grigorev Alexey Grigorev
Author Profile Icon Alexey Grigorev
Alexey Grigorev
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Table of Contents (12) Chapters Close

Preface 1. Recognizing traffic signs using Convnets 2. Annotating Images with Object Detection API FREE CHAPTER 3. Caption Generation for Images 4. Building GANs for Conditional Image Creation 5. Stock Price Prediction with LSTM 6. Create and Train Machine Translation Systems 7. Train and Set up a Chatbot, Able to Discuss Like a Human 8. Detecting Duplicate Quora Questions 9. Building a TensorFlow Recommender System 10. Video Games by Reinforcement Learning 11. Other Books You May Enjoy

Building GANs for Conditional Image Creation

Yann LeCun, Director of Facebook AI, has recently stated that "Generative Adversarial Networks is the most interesting idea in the last ten years in machine learning", and that is certainly confirmed by the elevated interest in academia about this deep learning solution. If you look at recent papers on deep learning (but also look at the leading trends on LinkedIn or Medium posts on the topic), there has really been an overproduction of variants of GANs.

You can get an idea of what a zoo the world of GANs has become just by glancing the continuously updated reference table, created by Hindu Puravinash, which can be found at https://github.com/hindupuravinash/the-gan-zoo/blob/master/gans.tsv or by studying the GAN timeline prepared by Zheng Liu, which can be found at https://github.com/dongb5/GAN-Timeline and can help you putting...

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