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adammenges / hackernewscorpus.py
Last active Aug 29, 2015
get hacker news corpus
View hackernewscorpus.py
# coding: utf-8
import requests
import os.path
import time
def multiple_tries(func, times, timeout):
for cnt in xrange(1, times + 1):
try:
return func()
except Exception, e:
View sklearn.py
import string, sklearn, random
from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer
from sklearn.svm import SVC
from sklearn.pipeline import Pipeline
from sklearn.grid_search import GridSearchCV
from sklearn.cross_validation import StratifiedKFold
def tok(m):
return m.split()
View gist:4643277
def fizzbuzz(n):
for i in xrange(1, n+1): print [i, 'Fizz', 'Buzz', 'FizzBuzz'][(i%3 == 0) + 2 * (i % 5 == 0)]
View shuffleCards.java
public void shuffleCards (int[] cards){
int temp, index;
for (int i = 0; i < cards.length; i++){
index = (int) (Math.random() * (cards.length - i)) + i;
temp = cards[i];
cards[i] = cards[index];
cards[index] = temp;
}
}
View question1-1.java
public boolean inUnique(string str) {
boolean[] chars = new boolean[256]; // Size only works with ASCII, increase otherwise.
for(int i=0; i<str.size(); i++){
if(chars[str.charAt(i)]) return false;
chars[str.charAt(i)] = true;
}
return true;
}
View problemcode.c
unsigned int i;
for(i=100; i<=0; --i)
print(i)
View question1-2.java
public boolean isUnique(string str) {
for(int i=0; i<str.size(); i++){
for(int j=0; j<str.size(); j++) {
if(i==j) continue;
else if(str.charAt(j) == str.charAt(i)) return false;
}
}
return true;
}
View validParentheses.rb
def validParentheses? str
a = []
str.each_char do |x|
if x == '('
a.push x
elsif x == ')'
return false if a.pop == nil
end
end
a.empty?
@adammenges
adammenges / FizzBuzz.py
Last active Jan 1, 2016
One liner FizzBuzz
View FizzBuzz.py
def fizzbuzz(n):
print "\n".join([('Fizz'*(not i%3) + 'Buzz'*(not i%5)) if ((not i%3) or (not i%5)) else str(i) for i in xrange(1, n+1)])
@adammenges
adammenges / min-char-rnn.py
Created Jan 6, 2017 — forked from karpathy/min-char-rnn.py
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
View min-char-rnn.py
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)