vvanirudh

# Drawn from https://gist.github.com/rocknrollnerd/c5af642cf217971d93f499e8f70fcb72 (in Theano)
# This is implemented in PyTorch
# Author : Anirudh Vemula

import torch
import torch.nn as nn
from torch.autograd import Variable
import numpy as np

from sklearn.datasets import fetch_mldata

xmfbit

import os
import torch
import torch.nn as nn
from torch.autograd import Variable
import torchvision.datasets as dset
import torchvision.transforms as transforms
import torch.nn.functional as F
import torch.optim as optim
## load mnist dataset
use_cuda = torch.cuda.is_available()

panovr

import argparse
import os
import shutil
import time

import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim

GilLevi

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns

Convolutional neural networks for emotion classification from facial images as described in the following work:

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015

Project page: http://www.openu.ac.il/home/hassner/projects/cnn_emotions/

If you find our models useful, please add suitable reference to our paper in your work.

ebenolson

FROM ubuntu:trusty

########################################
#
# openslide 3.4.1 image based on Ubuntu:trusty
#
#######################################

# Set Locale

hnykda

import pandas as pd  
from random import random

flow = (list(range(1,10,1)) + list(range(10,1,-1)))*100
pdata = pd.DataFrame({"a":flow, "b":flow})  
pdata.b = pdata.b.shift(9)  
data = pdata.iloc[10:] * random()  # some noise  

import numpy as np

mariozig

# Assume we are in your home directory
cd ~/

# Clone the repo from GitLab using the `--mirror` option
$ git clone --mirror git@your-gitlab-site.com:mario/my-repo.git

# Change into newly created repo directory
$ cd ~/my-repo.git

# Push to GitHub using the `--mirror` option.  The `--no-verify` option skips any hooks. 

bradwestfall

Get Instagram Images via JavaScript

Get API Info

You will need the user_id from the user. This is difficult to discover at Instagram but easy from this site http://jelled.com/instagram/lookup-user-id

I used http://jelled.com/instagram/access-token for the next few steps

You will also need an access token which ends up being difficult to obtain. Log into the account and go to their Developer Page.