doron2402

doron2402

# Predict how much tip will get per our clients age
# Using a simple linear regression model
dataset = read.csv('tip.csv')

library(caTools)
# choose random number for the see
set.seed(100)
# Split the dataset between test and train set
split = sample.split(dataset$Tip, SplitRatio = 2/3)
training_set = subset(dataset, split == TRUE)

doron2402

# Import python packages
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
# Load our dataset from a csv
dataset = pd.read_csv('tip.csv')
# Fetch the age column
age = dataset.iloc[:, :-1].values

doron2402

# import the dataset
dataset = read.csv('Data.csv')

# missing values
dataset$Age = ifelse(is.na(dataset$Age), 
                     ave(dataset$Age, FUN = function(x) mean(x, na.rm=TRUE)), 
                     dataset$Age)

dataset$Salary = ifelse(is.na(dataset$Salary),
                        ave(dataset$Salary, FUN = function(x) mean(x, na.rm = TRUE)),

doron2402

import pandas as pd
import sklearn as sk
# import the dataset
dataset = pd.read_csv(‘db.csv’)
# Load all columns into matrix but not the last ones
x = dataset.iloc[0:12,0:5].values
# Last column from the dataset
y = dataset.iloc[0:12,6].values
# Use the mean for fill missing data
imputer = sk.preprocessing.Imputer()

doron2402

const Query = ‘select * from users’;
const pool = server.plugins[‘hapi - plugin - pg’].pg;
pool.query(Query, (err, res) => { 
  if (err) {  //do something
     } 
  pool.end(); // this is important 
   
  return res;
});

doron2402

// index.js
‘
use strict’;
const Hapi = require(‘hapi’);
const Joi = require(‘joi’);

const server = new Hapi.Server();
server.connection({
  port: 3000,
  host: ‘localhost’

doron2402

AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Parameters: 
  NotificationEmail:
    Type: String
Resources:
  CloudTrailEventProcessing:
    Type: AWS::Serverless::Function
    Properties:
      Handler: handler

doron2402

version: 0.2

phases:
  install:
    commands:
      - echo Installing Mocha...
      - npm install -g mocha
  pre_build:
    commands:
      - echo Installing source NPM dependencies...

doron2402

'use strict';
 const Memwatch = require('memwatch-next');
 const Util = require('util');
 
 if (Config.env === 'production') {
   /**
    * Check for memory leaks
     */
    let hd = null;
    Memwatch.on('leak', (info) => {