ramansah

import { Component } from '@angular/core';

@Component({
  selector: 'income-query',
  template: `
    <div class='income-query'>
      <input #income_input type='text' value='{{income}}' class='income-box'/>
      <img (click)='breakup(income_input)' class='arrow-right' src='/resources/arrow-right.png'/>
    </div>
  `,

ramansah

from random import randint
TRAIN_SET_LIMIT = 1000
TRAIN_SET_COUNT = 100

TRAIN_INPUT = list()
TRAIN_OUTPUT = list()
for i in range(TRAIN_SET_COUNT):
    a = randint(0, TRAIN_SET_LIMIT)
    b = randint(0, TRAIN_SET_LIMIT)
    c = randint(0, TRAIN_SET_LIMIT)

ramansah

from sklearn.linear_model import LinearRegression

predictor = LinearRegression(n_jobs=-1)
predictor.fit(X=TRAIN_INPUT, y=TRAIN_OUTPUT)

ramansah

X_TEST = [[10, 20, 30]]
outcome = predictor.predict(X=X_TEST)
coefficients = predictor.coef_

print('Outcome : {}\nCoefficients : {}'.format(outcome, coefficients))

ramansah

cred_file = open('credentials.json', 'r')
cred_json = json.load(cred_file)

cred_file.close()
public_key = cred_json['public_key']
secret_key = cred_json['secret_key']

upwork_client = upwork.Client(public_key, secret_key)

ramansah

auth_url = upwork_client.auth.get_authorize_url()
# Opens a new tab in default web browser
webbrowser.open(url=auth_url, autoraise=True, new=2)
print 'Go to the mentioned URL : {}'.format(auth_url)

ramansah

verifier = raw_input('Enter Verifier: ')

(token, token_secret) = upwork_client.auth.get_access_token(verifier)

upwork_client = upwork.Client(
    public_key, secret_key,
    oauth_access_token=token,
    oauth_access_token_secret=token_secret)

ramansah

while True:
# Get all latest jobs
print '\nGetting Jobs at {} ...\n'.format(
    datetime.now().strftime('%H:%M'))
jobs = client.provider_v2.search_jobs(job_query)
current_jobs = set()

# Iterate every job
for job in jobs:

ramansah

import pandas as pd
from sklearn.tree import DecisionTreeClassifier

train_data = pd.read_csv('train.csv')
test_data = pd.read_csv('train.csv')

survived = train_data['Survived']
train_data.drop('Survived', axis=1, inplace=True)

model = DecisionTreeClassifier()

ramansah

def index
  @articles = Article.all.to_json(
    :only => [:id, :title, :status, :author]
  )
end

def publish
  article = Article.find(params[:id])
  article.publish
  render json: {