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deepgram
kur
Python2017–2017
deepgram / kur

kur

Descriptive Deep Learning

2Distinct people
2Mentions
0Explicit recommenders
824GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Descriptive Deep Learning

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:03:16 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by hour2 dated mentions

Observed mentions: 2017-01-18 09:27:12 UTC to 2017-01-18 22:50:48 UTC.

012017-01-18 09:00:00 UTC to 2017-01-18 10:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJan 18, 09:002017-01-18 10:00:00 UTC to 2017-01-18 11:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 11:00:00 UTC to 2017-01-18 12:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 12:00:00 UTC to 2017-01-18 13:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 13:00:00 UTC to 2017-01-18 14:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 14:00:00 UTC to 2017-01-18 15:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 15:00:00 UTC to 2017-01-18 16:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJan 18, 15:002017-01-18 16:00:00 UTC to 2017-01-18 17:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 17:00:00 UTC to 2017-01-18 18:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 18:00:00 UTC to 2017-01-18 19:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 19:00:00 UTC to 2017-01-18 20:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 20:00:00 UTC to 2017-01-18 21:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 21:00:00 UTC to 2017-01-18 22:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-18 22:00:00 UTC to 2017-01-18 23:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJan 18, 22:00

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jan 18, 09:002017-01-18 09:00:00 UTC2017-01-18 10:00:00 UTC101
Jan 18, 10:002017-01-18 10:00:00 UTC2017-01-18 11:00:00 UTC000
Jan 18, 11:002017-01-18 11:00:00 UTC2017-01-18 12:00:00 UTC000
Jan 18, 12:002017-01-18 12:00:00 UTC2017-01-18 13:00:00 UTC000
Jan 18, 13:002017-01-18 13:00:00 UTC2017-01-18 14:00:00 UTC000
Jan 18, 14:002017-01-18 14:00:00 UTC2017-01-18 15:00:00 UTC000
Jan 18, 15:002017-01-18 15:00:00 UTC2017-01-18 16:00:00 UTC000
Jan 18, 16:002017-01-18 16:00:00 UTC2017-01-18 17:00:00 UTC000
Jan 18, 17:002017-01-18 17:00:00 UTC2017-01-18 18:00:00 UTC000
Jan 18, 18:002017-01-18 18:00:00 UTC2017-01-18 19:00:00 UTC000
Jan 18, 19:002017-01-18 19:00:00 UTC2017-01-18 20:00:00 UTC000
Jan 18, 20:002017-01-18 20:00:00 UTC2017-01-18 21:00:00 UTC000
Jan 18, 21:002017-01-18 21:00:00 UTC2017-01-18 22:00:00 UTC000
Jan 18, 22:002017-01-18 22:00:00 UTC2017-01-18 23:00:00 UTC101

What Hacker News says

2 sources
Great questions! I'm the core maintainer of Kur. For a quick way to get it going, you can go to this link: http://kur.deepgram.com/install.html#kur-quick-install And scroll just a little bit to the “Quick Start For Using pip”. It has this code: pip install virtualenv # Make sure virtualenv is present virtualenv -p $(which python3) ~/kur-env # Create a Python 3 environment for Kur . ~/kur-env/bin/activate # Activate the Kur environment pip install kur # Install Kur kur --version # Check that everything works git clone https://github.com/deepgram/kur # Get the examples cd kur/examples # Change directories kur -v train mnist.yml # Start training! The key line there is where i
Read the rest
t mentions: virtualenv -p $(which python3) ~/kur-env This line grabs your Python 3 install and makes a virtual environment. The rest of the commands just move things around into a tiny environment so you’ll find yourself in a directory where you can just run: kur train mnist.yml Then you’ll be training. :) The list of dependencies is in "setup.py" in the repo--they are all Python packages. The reason you're probably getting the Python3 error is that you need to set up a virtual environment so that your system can isolate different versions of Python (and Python packages). In fact, if you use virtual environments, all the dependencies that get install are confined to that virtual environment, and won't affect the rest of your installation. Using virtual environments is definitely a Python "best practice," and if you've never done it before, we walk you through it in our "Quick Start" section of the documentation: https://kur.deepgram.com/install.html#kur-quick-install If you want to inspect the packages that are installed in the kur-env virtual environment, then (while in kur-env), just do: pip freeze And it will print out the installed python packages. You can join our gitter channel too if you need some more assistance! https://gitter.im/deepgram-kur/Lobby
In Show HN: Kur by Deepgram (YC S16) – Deep Learning Made Easy
Deepgram is open sourcing Kur (http://kur.deepgram.com)! Kur is the worlds first descriptive Deep Learning software. Think of a model, describe it in a simple YAML or JSON file, and train to get state-of-the-art results. There's no need to code. Why we built Kur: Prototyping DNNs is a slow process. Most people doing deep learning want to iterate and try out different model architectures and learn from others. It's hard to do this using barebones backends like TensorFlow/Theano or even the higher abstraction of software like Keras. Kur is not speech specific. It can be used for images (we supply two examples), speech (we supply one example and DG is open sourcing a new audio dataset with it, the DEEPGRAM10), text, etc. There are CNN layers, RNN, dense, dropout, batch norm, etc. to pick and choose from. The best part? Kur does all the plumb
Read the rest
ing! You want one input but two outputs? Not a problem, describe that model in Kur! We're really pumped to be releasing Kur and would love to answer questions if you've got em. Thanks! Deepgram AI Research Team http://kur.deepgram.com http://github.com/deepgram/kur http://kurhub.com
In Show HN: Kur by Deepgram (YC S16) – Deep Learning Made Easy

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