caffeine-potent

my_dict = dict({
      1     : "",
      2     : "",
      3     : "oyy",
      "oyy" : "",
      1990  : 's kid',
      2000  : "a",
      2014  : "b",
      2015  : "c",
      "foo" : "bar",

caffeine-potent

import math
import random


def categorical_draw(probs):
    '''
    if
    P(A) = .5
    P(B) = .2
    P(C) = .3

caffeine-potent

import math
import random


def categorical_draw(probs):
    '''
    if
    P(A) = .5
    P(B) = .2
    P(C) = .3

caffeine-potent

import numpy as np
class EpsGreedy()
  def __init__(self, number_of_bandits, epsilon, start_greedy= True):
    self.count = np.zeros(number_of_bandits)
    self.scores = np.array([int(!start_greedy)] * number of bandits)  
    self.epsilon = epsilon  
    self.bandit_count = number_of_bandits
  def select_arm():  
    choice = np.random.binomial(1,self.epsilon):
    if choice = 1: #EXPLORE

caffeine-potent

class B:
    def __init__(self):
        self.data = []
    def update(self, row):
        for r in row:
            self.data.append(r)
    def finalize(self):
        return np.reshape(self.data, newshape=(len(self.data)/5, 5))
    
ax = B()

caffeine-potent