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@mbostock
mbostock / README.md
Last active June 7, 2023 18:33
Underscore’s Equivalents in D3

Collections

each(array)

Underscore example:

_.each([1, 2, 3], function(num) { alert(num); });
@aflaxman
aflaxman / mpl_cfaces.py
Created November 9, 2012 01:12
Chernoff Faces in Python with Matplotlib
from pylab import *
def cface(ax, x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16,x17,x18):
# x1 = height of upper face
# x2 = overlap of lower face
# x3 = half of vertical size of face
# x4 = width of upper face
# x5 = width of lower face
# x6 = length of nose
# x7 = vertical position of mouth
@lucasb-eyer
lucasb-eyer / ILSVRC2012_ids.json
Last active June 10, 2017 02:37
Data for Beacon8 Pretrained Imagenet example
{
"n02112350": 148,
"n04344873": 311,
"n01692333": 470,
"n03459775": 725,
"n04133789": 751,
"n01871265": 214,
"n04366367": 681,
"n03891332": 527,
"n03085013": 543,
@hussius
hussius / ae_toy_example.py
Last active June 28, 2019 17:12
Toy example of single-layer autoencoder in TensorFlow
import tensorflow as tf
import numpy as np
import math
#import pandas as pd
#import sys
input = np.array([[2.0, 1.0, 1.0, 2.0],
[-2.0, 1.0, -1.0, 2.0],
[0.0, 1.0, 0.0, 2.0],
[0.0, -1.0, 0.0, -2.0],
@jfsantos
jfsantos / example_hdf5matrix.py
Last active May 11, 2020 06:57
from keras.models import Sequential
from keras.layers import Dense
from keras.utils.io_utils import HDF5Matrix
import numpy as np
def create_dataset():
import h5py
X = np.random.randn(200,10).astype('float32')
y = np.random.randint(0, 2, size=(200,1))
f = h5py.File('test.h5', 'w')
@letmaik
letmaik / index.html
Created October 7, 2016 10:07
Leaflet GridLayer example with Canvas
<!DOCTYPE html>
<html>
<head>
<title>GridLayer Test</title>
<meta charset="utf-8" />
<link rel="stylesheet" href="https://unpkg.com/leaflet@1.0.1/dist/leaflet.css" />
<style>
body {
padding: 0;
margin: 0;
@anthonydelgado
anthonydelgado / emoji array
Created October 30, 2016 04:56
["✌","😂","😝","😁","😱","👉","🙌","🍻","🔥","🌈","☀","🎈","🌹","💄","🎀","⚽","🎾","🏁","😡","👿","🐻","🐶","🐬","🐟","🍀","👀","🚗","🍎","💝","💙","👌","❤","😍","😉","😓","😳","💪","💩","🍸","🔑","💖","🌟","🎉","🌺","🎶","👠","🏈","⚾","🏆","👽","💀","🐵","🐮","🐩","🐎","💣","👃","👂","🍓","💘","💜","👊","💋","😘","😜","😵","🙏","👋","🚽","💃","💎","🚀","🌙","🎁","⛄","🌊","⛵","🏀","🎱","💰","👶","👸","🐰","🐷","🐍","🐫","🔫","👄","🚲","🍉","💛","💚"]
@poolio
poolio / Adversarial variational bayes toy example.ipynb
Last active August 1, 2023 00:59
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@soumith
soumith / dcgan.py
Created January 30, 2017 03:25 — forked from anonymous/dcgan.py
import torch
import torch.nn as nn
import torch.nn.parallel
class DCGAN_D(nn.Container):
def __init__(self, isize, nz, nc, ndf, ngpu, n_extra_layers=0):
super(DCGAN_D, self).__init__()
self.ngpu = ngpu
assert isize % 16 == 0, "isize has to be a multiple of 16"
@hiroyachiba
hiroyachiba / classifier_from_little_data_script_3.py
Last active January 21, 2018 22:51 — forked from fchollet/classifier_from_little_data_script_3.py
Fine-tuning a Keras model.
'''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/