aka7h

from __future__ import print_function

import os

import numpy as np
from keras.layers import RepeatVector
from keras.layers.core import Dropout
from keras.layers.recurrent import LSTM
from keras.models import Sequential
from keras.models import load_model

aka7h

from numpy.linalg import solve

class ExplicitMF():
    def __init__(self, 
                 ratings, 
                 n_factors=40, 
                 item_reg=0.0, 
                 user_reg=0.0,
                 verbose=False):
        """

aka7h

#forecasting the number of new cases in EColi

data('ecoli', package = "tscount")
head(ecoli)

class(ecoli)

data <- as.numeric(unlist(ecoli[3]))
data <- ts(matrix(data),start = c(2001,1),end = c(2013,20), frequency = 52)
data

aka7h

require(pracma)
require(ridge)

train_valid_shuffle <- read.csv('wk3_kc_house_train_valid_shuffled.csv')
test_v <- read.csv('wk3_kc_house_test_data.csv')

polynomial_sframe <- function(feature , degree){
  df_frame = data.frame('power_1' = feature)
  if(degree > 2){
    for(i in 2:degree){

aka7h

regression_gradient_decent <- function(feature_matrix, output, initial_weight,step_size, tolerance){
    converged = FALSE
    weights = initial_weight
    while(!(converged)){
        predictions = predict_output(feature_matrix, weights)
        
        err = predictions - output
        gradient_sum_square = 0
        for(i in 1:length(weights)){
            derivative =  feature_derivative(err,feature_matrix[,i])

aka7h

n = int(raw_input())
c=[]
c.append(n)
def a(n):
    global c
    if n==1:
        return
    if n%2==0:
        c.append(n/2)
        a(n/2)

aka7h

# Input
# 9
# 1 2 3 4 5 6 7 8 9
# Output
# 987654321
 

n = int(raw_input())
d = [i for i in raw_input().split()]
if d.count('0') != n:

aka7h

elem_count = int(raw_input())
el= [i for i in raw_input().split()]
for x in xrange(1,len(el)-1):
    j=x
    while j>0 and el[j-1]>el[j]:
        el[j],el[j-1] = el[j-1],el[j]
        j-=1
        print el

aka7h

n = int(raw_input())
c = [str(x) for x in xrange(0,10)]
for i in xrange(n):
    line = [x for x in raw_input()]
    r = set(c) - set(line)
    for x in r:
        print x
    

aka7h

n = int(raw_input())
for i in xrange(n):
    w = raw_input()
    if w[::1] == w[::-1]:
        print "true"
    else:
        print "false"