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Practical Deep Learning for Cloud and Mobile by Meher Kasam, Siddha Ganju, Anirudh Koul

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Chapter 7. Not Hotdog with Keras & CoreML

A Note for Early Release Readers

This will be the 12th chapter of the final book.

If you have comments about how we might improve the content and/or examples in this book, or if you notice missing material, please reach out to the authors at practicaldlbook@gmail.com.

“I’m a rich”, said Jian-Yang, a newly minted millionaire in an interview with Bloomberg. What did he do? He created the Not Hotdog app and made the world “a better place”.

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Figure 7-1. Jian Yang being interviewed by Bloomberg News after Periscope acquires his “Not Hotdog” technology. Source: HBO.

To the few of you who may be confused (including a third of the authors of this book), we are making a reference to HBO’s Silicon Valley show where one of the characters is tasked with making SeeFood - the “Shazam of food”. It was meant to classify pictures of food and give recipes and nutritional information. Hilariously, the app ends up being good only for recognizing hot dogs. Anything else would be classified as ‘Not Hotdog’.

There are a few reasons we chose to reference this fictitious app. It’s very much part of popular culture and something many people can easily relate to. It’s an exemplar - easy enough to build, yet powerful enough to see the magic of deep learning in a real-world application. It is also very trivially generalizable to recognize more than one class of items. ...

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