MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

JamieMason

Unfollow everyone on twitter.com

1. Go to https://twitter.com/YOUR_USER_NAME/following
2. Open the Developer Console. (COMMAND+ALT+I on Mac)
3. Paste this into the Developer Console and run it

// Unfollow everyone on twitter.com, by Jamie Mason (https://twitter.com/fold_left)
// https://gist.github.com/JamieMason/7580315
//

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

joelouismarino

from __future__ import print_function
import imageio
from PIL import Image
import numpy as np
import keras

from keras.layers import Input, Dense, Conv2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, Concatenate, Reshape, Activation
from keras.models import Model
from keras.regularizers import l2
from keras.optimizers import SGD

pylover

#! /usr/bin/env python3
"""Fixing bluetooth stereo headphone/headset problem in debian distros.

Workaround for bug: https://bugs.launchpad.net/ubuntu/+source/indicator-sound/+bug/1577197
Run it with python3.5 or higher after pairing/connecting the bluetooth stereo headphone.

This will be only fixes the bluez5 problem mentioned above .

Licence: Freeware

brotherofken

# In[]
import gym
import numpy as np
import theano
import theano.tensor as T
import lasagne
import sklearn.preprocessing
np.set_printoptions(precision=2)

sunskyhsh

def qlearning(env, policy, num_iter1, alpha, gamma):
    actions = policy.actions
    for i in xrange(len(policy.theta)):
        policy.theta[i] = 0.1

    for iter1 in xrange(num_iter1):
        s_f       = env.reset()
        a         = policy.epsilon_greedy(s_f)
        count     = 0
        t         = False

yossorion

What I Wish I'd Known About Equity Before Joining A Unicorn

Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.

This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would

jihunchoi

def _sequence_mask(sequence_length, max_len=None):
    if max_len is None:
        max_len = sequence_length.data.max()
    batch_size = sequence_length.size(0)
    seq_range = torch.range(0, max_len - 1).long()
    seq_range_expand = seq_range.unsqueeze(0).expand(batch_size, max_len)
    seq_range_expand = Variable(seq_range_expand)
    if sequence_length.is_cuda:
        seq_range_expand = seq_range_expand.cuda()
    seq_length_expand = (sequence_length.unsqueeze(1)

ahmedhosny

import nrrd # pip install pynrrd
import nibabel as nib # pip install nibabel
import numpy as np

# load nrrd 
_nrrd = nrrd.read('/path/to/nrrd.nrrd')
data = _nrrd[0]
header = _nrrd[1]
print data.shape, header