99.3% accuracy is not that great. Currently the best performer on this data set has 99.77% accuracy: http://yann.lecun.com/exdb/mnist/
What is the human accuracy on this data set?
Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]
11–20 of 37 posts
Re: Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]
#1299.3% accuracy is not that great. Currently the best performer on this data set has 99.77% accuracy: http://yann.lecun.com/exdb/mnist/
I wonder, is there a good reason why these accuracies are reported on a logscale by convention (say, as power of 2 from 50%)?
Re: Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]
#13Although TensorFlow/Keras allows anyone to implement Deep Learning easily, that doesn't mean that they will get hired for a relevant job position without a PhD. Most Deep Learning jobs, and even relatively mundane Data Scientist jobs nowadays, want a PhD from my experience. There is a surplus of Statistics/CS PhDs, why would a company hire someone without one if they do not have to? Without a relevant job position, k…
I have seen this from multiple angles.
I used to teach at a data science bootcamp where many of the students got hired by big companies.
I've also been running a deep learning startup for the last few years and have hired quite a few people.
Many of our team don't have phds but can still write backprop code for even complex modules like inception among other things. A lot of my students didn't have phds either.
A few of us (me included) are self taught. I've also coauthored the largest oreilly book on deep learning: http://shop.oreilly.com/product/0636920035343.do
1 piece of advice I would offer is building something that differentiates you from the rest. Many of these "medium thought pieces" you're talking about are actually very cool applications of deep learning. If you want to get hired for these kinds of roles, I would demonstrate you understand how to build things with deep learning. The litmus test I would also look for is "I trained a net from scratch and innovated in x way". Honestly, there's a rare amount of talent out there that can do well at software engineering as well as deep learning. I'm not convinced a phd is a hard requirement.
I get that recruiters at these larger companies definitely tend to look for the buzz words and often can't tell the difference so it's definitely harder going the traditional route.
Tech hiring also tends to be a networking thing as much as it is buzz word bingo no matter what field you're in. If you can network a bit and build something cool that demonstrates an understanding of deep learning I don't see the problem.
Re: Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]
#14Although TensorFlow/Keras allows anyone to implement Deep Learning easily, that doesn't mean that they will get hired for a relevant job position without a PhD. Most Deep Learning jobs, and even relatively mundane Data Scientist jobs nowadays, want a PhD from my experience. There is a surplus of Statistics/CS PhDs, why would a company hire someone without one if they do not have to? Without a relevant job position, k…
I have seen this from multiple angles. I used to teach at a data science bootcamp where many of the students got hired by big companies. I've also been running a deep learning startup for the last few years and have hired quite a few people. Many of our team don't have phds but can still write backprop code for even complex modules like inception among other things. A lot of my students didn't have phds either. A few…
Yeah, I'm gonna piggy back on this comment. Deep Learning was really introduced to the public 4 years ago. That's not a lot of time....
Re: Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]
#15[deleted]
Re: Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]
#16Although TensorFlow/Keras allows anyone to implement Deep Learning easily, that doesn't mean that they will get hired for a relevant job position without a PhD. Most Deep Learning jobs, and even relatively mundane Data Scientist jobs nowadays, want a PhD from my experience. There is a surplus of Statistics/CS PhDs, why would a company hire someone without one if they do not have to? Without a relevant job position, k…
> There is a surplus of Statistics/CS PhDs, why would a company hire someone without one if they do not have to? I thought it was a negative to have a PhD in SV?
I'm not sure if you're being sarcastic or not, but I don't think this is at all true at the types of companies that would be hiring deep learning experts in any significant quantity.
Even outside of "hot" research topics, large companies and startups doing technically interesting things recruit heavily out of top PhD programs. Many companies even have different hiring processes for Ph.D. candidates, even for job positions that don't require or recommend a Ph.D., which suggests those companies evaluate Ph.D. candidates differently (and therefore view them as a different sort of asset).
Re: Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]
#17Earlier quoted context omitted.
I have seen this from multiple angles. I used to teach at a data science bootcamp where many of the students got hired by big companies. I've also been running a deep learning startup for the last few years and have hired quite a few people. Many of our team don't have phds but can still write backprop code for even complex modules like inception among other things. A lot of my students didn't have phds either. A few…
Yeah, I'm gonna piggy back on this comment. Deep Learning was really introduced to the public 4 years ago. That's not a lot of time....
It's been around for quite a long time though. Neural nets themselves have seen multiple hype cycles now. See the history of CIFAR.
I would maybe rephrase this as "Machine learning really just became mainstream recently and now everyone wants in".
If you are talking about say: recruiters, they will always tend to piggy back on buzz words. They don't really learn the technology themselves. Requiring a phd and some of these other things that are being talked about is a general "data science problem".
I can't count how many candidates I've seen applying to companies that got turned down for jobs because they just went through the traditional HR funnel. Your best bet as I said earlier is just to network.
The worst parts of getting a deep learning job are the same ones that plague every tech position out there.
Re: Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]
#18This is a great tutorial for beginners. His sample code[1] is much better than the MNIST tutorials on the Tensorflow page, especially those visualizations.
[1] https://github.com/martin-gorner/tensorflow-mnist-tutorial/
Re: Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]
#19Although TensorFlow/Keras allows anyone to implement Deep Learning easily, that doesn't mean that they will get hired for a relevant job position without a PhD. Most Deep Learning jobs, and even relatively mundane Data Scientist jobs nowadays, want a PhD from my experience. There is a surplus of Statistics/CS PhDs, why would a company hire someone without one if they do not have to? Without a relevant job position, k…
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Re: Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]
#2099.3% accuracy is not that great. Currently the best performer on this data set has 99.77% accuracy: http://yann.lecun.com/exdb/mnist/
99.3% is pretty good for a one hour lecture that begins with a single-layer network.