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Identifying dog breeds using Keras

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Re: Identifying dog breeds using Keras

#11

Post by eftychis »

curiousgal wrote: post #2

Nothing impressive, existing architectures were used, InceptionV3, Xception and InceptionResNetV2. Fine-tuning those models resulted in a slightly worse accuracy.

Still it seems like a good write up. Yes, it is not innovative, it provides a good presentation and "here's how I solved this every day, company problem." I think this has a benefit in the Data science. Yes, it glosses over the retrieving and preparing your data section, which I feel is the most work in these problems. However, it gives an idea of how to combine your knowledge and think as a new Data Scientist. So I think it is helpful to some people. As other people said there is a plethora of similar articles in other Software Engineering fields that rise consistently in the front page of Hackernews.

Re: Identifying dog breeds using Keras

#12

Post by doggo_ »

bcheung wrote: post #7
ageitgey wrote: post #5

Machine learning is still considered "new" or "difficult" so people often respond to posts like this with comments like the one that says "Nothing impressive, existing architectures were used". Writers only get enthusiasm if they raise a benchmark with a brand new approach. For researchers and people spend a lot of time on ML, I totally get that. There isn't anything new here. In fact, I correctly guessed nearly the…

Agreed. There's too much of an academic paper culture around ML. It makes the field very unapproachable. It's as if people don't actually use it for anything practical and they only care about the science and math. It is getting better though. It's great to see people post articles like this and even if it has been done before seeing different approaches and seeing it written in different ways goes a long ways toward…

It's definitely getting better. With fast.ai, and Tensorflow coming with examples and docs to get started, I was able to make a proof of concept in a few hours to solve a real problem for real money.

It feels like we are on the cusp of non-experts being able to get real results and them being able to improve on classifiers for their domain. It almost feels like right before Rails took the world by storm.

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