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@Mistobaan
Mistobaan / tensorflow_cuda_osx.md
Last active July 25, 2023 18:54
How to enable cuda support for tensor flow on Mac OS X (Updated on April:2016 Tensorflow 0.8)

These instructions will explain how to install tensorflow on mac with cuda enabled GPU suport. I assume you know what tensorflow is and why you would want to have a deep learning framework running on your computer.

Prerequisites

Make sure to update your homebrew formulas

brew update
@FloorD
FloorD / gist:944d152fdd655cae03e8
Last active August 29, 2015 14:19
A recap of ROSSConf Vienna, April 25 2015

###The ROSSConf project, or: helping Open Source help Open Source

Last April Saturday ROSSConf Vienna took place. Sixty registered participants, some loose canons, 5 projects, 6 maintainers, 8-ish team members, 1 baby all in one coworking space. Here's what happened.

*credit: Manuel Gruber*

####In the beginning October last year, at arrrrcamp, I came up with the concept for ROSSConf. Having attended 1001 tech conferences (I haven't kept count) I concluded that I'm always missing something. I found myself listening to a talk and wishing I could contribute to the project discussed but the internet connection wasn't sufficient for cloning the repo, nor was there time to hack on the project as the next talk was about to start. And, I figured, I'd need some time to get into the project and the contributing etiquette before being able to contribute.

Linux Backup Solutions

I've been looking for the best Linux backup system, and also reading lots of HN comments.

Instead of putting pros and cons of every backup system I'll just list some deal-breakers which would disqualify them.

Also I would like that you, the HN community, would add more deal breakers for these or other backup systems if you know some more and at the same time, if you have data to disprove some of the deal-breakers listed here (benchmarks, info about something being true for older releases but is fixed on newer releases), please share it so that I can edit this list accordingly.

Bacula (from the Why section on Burp)

  • Too complex to configure
  • Stores catalog separate from backups, need to backup catalog
@drkarl
drkarl / gist:739a864b3275e901d317
Last active October 17, 2023 10:43
Ask HN: Best Linux server backup system?

Linux Backup Solutions

I've been looking for the best Linux backup system, and also reading lots of HN comments.

Instead of putting pros and cons of every backup system I'll just list some deal-breakers which would disqualify them.

Also I would like that you, the HN community, would add more deal breakers for these or other backup systems if you know some more and at the same time, if you have data to disprove some of the deal-breakers listed here (benchmarks, info about something being true for older releases but is fixed on newer releases), please share it so that I can edit this list accordingly.

  • It has a lot of management overhead and that's a problem if you don't have time for a full time backup administrator.
@kmikael
kmikael / eject.sh
Created August 9, 2014 09:17
Eject every disk whose ejectable is true (shell script)
osascript -e 'tell application "Finder" to eject (every disk whose ejectable is true)'
@anikalindtner
anikalindtner / gist:9524950
Last active March 1, 2023 11:52
Workshops/Mailinglists/Lists
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@dan-blanchard
dan-blanchard / .1.miniconda.md
Last active December 11, 2019 22:38
Quicker Travis builds that rely on numpy and scipy using Miniconda

For ETS's SKLL project, we found out the hard way that Travis-CI's support for numpy and scipy is pretty abysmal. There are pre-installed versions of numpy for some versions of Python, but those are seriously out of date, and scipy is not there are at all. The two most popular approaches for working around this are to (1) build everything from scratch, or (2) use apt-get to install more recent (but still out of date) versions of numpy and scipy. Both of these approaches lead to longer build times, and with the second approach, you still don't have the most recent versions of anything. To circumvent these issues, we've switched to using Miniconda (Anaconda's lightweight cousin) to install everything.

A template for installing a simple Python package that relies on numpy and scipy using Miniconda is provided below. Since it's a common s

## How to Use:
from radar import radar_graph
labels = ['v1', 'v2', 'v3', 'v4', 'v5', 'v6', 'v7', 'v8', 'v9']
values = [1, 1, 2, 7, 4, 0, 3, 10, 6]
optimum = [5, 3, 2, 4, 5, 7, 5, 8, 5]
radar_graph(labels, values, optimum)
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