saip

10 ms·

1.
Automating Customer Support Using NLP and Deep Learning(blog.floydhub.com)
6 points by saip 8y ago|1 comments
2.
Thanksgiving Cousin Classifier: Recognize Relatives Using Deep Learning(blog.floydhub.com)
2 points by saip 8y ago|0 comments
3.
Colorizing and Restoring Old Images with Deep Learning(blog.floydhub.com)
1 points by saip 8y ago|0 comments
4.
by saip 8y ago
Access to parallel corpora is a limiting factor in general. A good way to train a language translator is to use an open source dataset (several here http://opus.nlpl.eu/ ) to train a base model, and then fine-tune it with a
5.
Building a language translator from scratch with deep learning(blog.floydhub.com)
226 points by saip 8y ago|34 comments
6.
Asking questions to images with Deep Learning and visual question answering(blog.floydhub.com)
2 points by saip 8y ago|0 comments
7.
Deep learning beginner to expert: techniques from Fast.ai(blog.floydhub.com)
114 points by saip 8y ago|10 comments
8.
The Machine Learning reproducibility crisis(petewarden.com)
4 points by saip 9y ago|0 comments
9.
Teaching My Cozmo Robot with Tensorflow(blog.floydhub.com)
6 points by saip 9y ago|1 comments
10.
Learning multiple tasks with gradient descent(medium.com)
2 points by saip 9y ago|0 comments
11.
Generating six-pack abs with Tensorflow(blog.floydhub.com)
13 points by saip 9y ago|10 comments
12.
by saip 9y ago
A GAN style approach to learning and generating variants could be interesting as well. It could generate a couple of hundred plausible versions. Then you have another network that is trained to differentiate between fake and real colored ph
13.
by saip 9y ago
Agreed. I imagine this has applications in compression as well. You could stream a movie (or a football game) in black and white and enable each device to color it on the spot. A similar technique could also be done for HD/3D/VR.
14.
Colorizing black and white photos with deep learning(blog.floydhub.com)
247 points by saip 9y ago|51 comments
15.
by saip 9y ago
Hey, thanks! I'm one of the co-founders at FloydHub. Our focus has been on individual data scientists thus far. We'll be rolling out a teams plan soon since folks doing deep learning at work (with on-prem or cloud infra) tend to r
16.
by saip 9y ago
FloydHub | Cloud Infrastructure Engineer | San Francisco, CA | Onsite | Full-time | Salary: 100k-125k (0.5%-1% equity) | https://floydhub.com FloydHub (YC W17) is building a Heroku for deep learning. We enable data scientists to
17.
by saip 9y ago
Likewise, any cloud infrastructure engineers in the Bay Area that might be looking, shoot me a mail - sai at floydhub dot com
18.
Coding the History of Deep Learning(blog.floydhub.com)
256 points by saip 9y ago|50 comments
19.
Should I buy my own GPUs for deep learning?(blog.floydhub.com)
5 points by saip 9y ago|2 comments
20.
by saip 9y ago
DevOps is indeed a huge bottleneck in deep learning. Provisioning machines, installing drivers and packages and managing their dependency hell distracts focus from the core deep learning. At FloydHub (I'm a co-founder), we're buil
21.
by saip 9y ago
FloydHub (YC W17) is building a Heroku for deep learning. Data scientists can train and deploy deep learning models in the cloud with a few simple commands and without any of the DevOps hassles. Instead of worrying about provisioning GPUs,
22.
FloydHub (YC W17, Heroku for Deep Learning) Is Hiring Head of Growth, Engineers
1 points by saip 9y ago
23.
by saip 10y ago
If you want to try out fastText without having to do any local setup, see https://github.com/floydhub/fastText . FloydHub[1] is a deep learning PaaS for training and deploying DL models in the cloud with zero setup. [1]
24.
by saip 10y ago
Hey! Glad you brought this up. We've gotten quite a few requests from students enrolled in Udacity courses and have been helping get them set up & run their class projects on Floyd. Here's our instructions for the Self Driving
25.
by saip 10y ago
Thanks - fixed now! :)
26.
by saip 10y ago
When we started out, we were just building a bot ( droid ) to manage our deep learning workflows (scheduling jobs, logging results, etc.) So, Flow + Droid => Floyd. Also, a hat tip to one of my favorite bands :)
27.
by saip 10y ago
You mean bash on Windows? The CPU version of dl-docker will work on Windows! But unfortunately, the GPU version does not. You would need GPU passthrough, which is currently not supported. See https://github.com/NVIDIA/n
28.
by saip 10y ago
We’ve definitely felt the bane of forgetting to turn off some really expensive GPU instances. Efficient scheduling and spinning instances up/down as required is one of the first things we built to cut down on the costs. Git is an apt a
29.
by saip 10y ago
That’s awesome! ML to some extent, and DL to a large extent are still not considered mainstream enough by many. The big players (Google, Facebook, Baidu) seem to recognize this and invest appropriately, but the others not so much yet. That’
30.
by saip 10y ago
Our Individual plan has no monthly fees, and is purely pay-per-use @ <50% of AWS pricing.

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