katef

#!/usr/bin/awk -f

# This program is a copy of guff, a plot device. https://github.com/silentbicycle/guff
# My copy here is written in awk instead of C, has no compelling benefit.
# Public domain. @thingskatedid

# Run as awk -v x=xyz ... or env variables for stuff?
# Assumptions: the data is evenly spaced along the x-axis

# TODO: moving average

alexjc

Specific Papers

• https://arxiv.org/abs/1505.07376

  Texture Synthesis Using Convolutional Neural Networks
• https://arxiv.org/abs/1508.06576

  A Neural Algorithm of Artistic Style
• https://arxiv.org/abs/1603.03417

  Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
• https://arxiv.org/abs/1701.02096

  Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Texture Synthesis

bmaupin

ⓘ This list is not meant to be exhaustive and is not guaranteed to be maintained. See the comments for updates and alternative options.

(Items in bold indicate possible concerns)

	Keycloak	WSO2 Identity Server	Gluu	CAS	OpenAM	Shibboleth IdP
OpenID Connect/OAuth support	yes	yes	yes	yes	yes	yes
Multi-factor authentication	yes	yes	yes	yes	yes	yes
Admin UI	yes	yes	yes	yes	yes	no
OpenJDK support	yes	yes	partial²	yes

MatthieuBizien

# coding: utf-8

import logging
import re
from collections import Counter

import numpy as np
import torch
from sklearn.datasets import fetch_20newsgroups
from torch.autograd import Variable

Pakillo

https://github.com/brentthorne/posterdown

https://github.com/rstudio/pagedown

https://github.com/GerkeLab/betterposter

https://github.com/pzhaonet/postr

https://github.com/odeleongt/postr

AustinRochford

mcnees

%%-----------------------------------------------------------------------
%% Make your own quadrille, graph, hex, etc paper!
%% Uses the pgf/TikZ package for LaTeX, which should be part of
%% any modern TeX installation.
%% Email: mcnees@gmail.com 
%% Twitter: @mcnees
%%-----------------------------------------------------------------------

\documentclass[11pt]{article}

Icelandjack

Reddit discussion.

Disclaimer 1: Type classes are great but they are not the right tool for every job. Enjoy some balance and balance to your balance.

Disclaimer 2: I should tidy this up but probably won’t.

Disclaimer 3: Yeah called it, better to be realistic.

Type classes are a language of their own, this is an attempt to document features and give a name to them.

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

danijar

# Working example for my blog post at:
# http://danijar.com/variable-sequence-lengths-in-tensorflow/
import functools
import sets
import tensorflow as tf
from tensorflow.models.rnn import rnn_cell
from tensorflow.models.rnn import rnn


def lazy_property(function):