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import tensorflow as tf | |
tf.logging.set_verbosity(tf.logging.ERROR) | |
from tensorflow.examples.tutorials.mnist import input_data | |
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) | |
image_size = 28 | |
labels_size = 10 |
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// Create mock features for evaluating AWS ML performance | |
const fs = require('fs'); | |
let header = []; | |
['training', 'batch-prediction'] | |
.map(s => { | |
'abcdefghijklmnopqrstuvwxyz' |
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{ | |
"version" : "1.0", | |
"rowId" : null, | |
"rowWeight" : null, | |
"targetAttributeName" : "t", | |
"dataFormat" : "CSV", | |
"dataFileContainsHeader" : true, | |
"attributes" : [ { | |
"attributeName" : "a0", | |
"attributeType" : "NUMERIC" |
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PassengerId | Survived | Pclass | Lname | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 0 | 3 | Braund | Mr. Owen Harris | male | 22 | 1 | 0 | A/5 21171 | 7.25 | S | ||
2 | 1 | 1 | Cumings | Mrs. John Bradley (Florence Briggs Thayer) | female | 38 | 1 | 0 | PC 17599 | 71.2833 | C85 | C | |
3 | 1 | 3 | Heikkinen | Miss. Laina | female | 26 | 0 | 0 | STON/O2. 3101282 | 7.925 | S | ||
4 | 1 | 1 | Futrelle | Mrs. Jacques Heath (Lily May Peel) | female | 35 | 1 | 0 | 113803 | 53.1 | C123 | S | |
5 | 0 | 3 | Allen | Mr. William Henry | male | 35 | 0 | 0 | 373450 | 8.05 | S | ||
6 | 0 | 3 | Moran | Mr. James | male | 0 | 0 | 330877 | 8.4583 | Q | |||
7 | 0 | 1 | McCarthy | Mr. Timothy J | male | 54 | 0 | 0 | 17463 | 51.8625 | E46 | S | |
8 | 0 | 3 | Palsson | Master. Gosta Leonard | male | 2 | 3 | 1 | 349909 | 21.075 | S | ||
9 | 1 | 3 | Johnson | Mrs. Oscar W (Elisabeth Vilhelmina Berg) | female | 27 | 0 | 2 | 347742 | 11.1333 | S |
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fixed acidity | volatile acidity | citric acid | residual sugar | chlorides | free sulfur dioxide | total sulfur dioxide | density | pH | sulphates | alcohol | quality | |
---|---|---|---|---|---|---|---|---|---|---|---|---|
7.4 | 0.7 | 0 | 1.9 | 0.076 | 11 | 34 | 0.9978 | 3.51 | 0.56 | 9.4 | 5 | |
7.8 | 0.88 | 0 | 2.6 | 0.098 | 25 | 67 | 0.9968 | 3.2 | 0.68 | 9.8 | 5 | |
7.8 | 0.76 | 0.04 | 2.3 | 0.092 | 15 | 54 | 0.997 | 3.26 | 0.65 | 9.8 | 5 | |
11.2 | 0.28 | 0.56 | 1.9 | 0.075 | 17 | 60 | 0.998 | 3.16 | 0.58 | 9.8 | 6 | |
7.4 | 0.7 | 0 | 1.9 | 0.076 | 11 | 34 | 0.9978 | 3.51 | 0.56 | 9.4 | 5 | |
7.4 | 0.66 | 0 | 1.8 | 0.075 | 13 | 40 | 0.9978 | 3.51 | 0.56 | 9.4 | 5 | |
7.9 | 0.6 | 0.06 | 1.6 | 0.069 | 15 | 59 | 0.9964 | 3.3 | 0.46 | 9.4 | 5 | |
7.3 | 0.65 | 0 | 1.2 | 0.065 | 15 | 21 | 0.9946 | 3.39 | 0.47 | 10 | 7 | |
7.8 | 0.58 | 0.02 | 2 | 0.073 | 9 | 18 | 0.9968 | 3.36 | 0.57 | 9.5 | 7 |
We can't make this file beautiful and searchable because it's too large.
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age,job,marital,education,default,housing,loan,contact,month,day_of_week,duration,campaign,pdays,previous,poutcome,emp_var_rate,cons_price_idx,cons_conf_idx,euribor3m,nr_employed,y | |
44,blue-collar,married,basic.4y,unknown,yes,no,cellular,aug,thu,210,1,999,0,nonexistent,1.4,93.444,-36.1,4.963,5228.1,0 | |
53,technician,married,unknown,no,no,no,cellular,nov,fri,138,1,999,0,nonexistent,-0.1,93.2,-42,4.021,5195.8,0 | |
28,management,single,university.degree,no,yes,no,cellular,jun,thu,339,3,6,2,success,-1.7,94.055,-39.8,0.729,4991.6,1 | |
39,services,married,high.school,no,no,no,cellular,apr,fri,185,2,999,0,nonexistent,-1.8,93.075,-47.1,1.405,5099.1,0 | |
55,retired,married,basic.4y,no,yes,no,cellular,aug,fri,137,1,3,1,success,-2.9,92.201,-31.4,0.869,5076.2,1 | |
30,management,divorced,basic.4y,no,yes,no,cellular,jul,tue,68,8,999,0,nonexistent,1.4,93.918,-42.7,4.961,5228.1,0 | |
37,blue-collar,married,basic.4y,no,yes,no,cellular,may,thu,204,1,999,0,nonexistent,-1.8,92.893,-46.2,1.327,5099.1,0 | |
39,blue-collar,divorced,basic.9y,no,yes,no,cel |
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Sex | Length | Diam | Height | Whole | Shucked | Viscera | Shell | Rings | |
---|---|---|---|---|---|---|---|---|---|
M | 0.455 | 0.365 | 0.095 | 0.514 | 0.2245 | 0.101 | 0.15 | 15 | |
M | 0.35 | 0.265 | 0.09 | 0.2255 | 0.0995 | 0.0485 | 0.07 | 7 | |
F | 0.53 | 0.42 | 0.135 | 0.677 | 0.2565 | 0.1415 | 0.21 | 9 | |
M | 0.44 | 0.365 | 0.125 | 0.516 | 0.2155 | 0.114 | 0.155 | 10 | |
I | 0.33 | 0.255 | 0.08 | 0.205 | 0.0895 | 0.0395 | 0.055 | 7 | |
I | 0.425 | 0.3 | 0.095 | 0.3515 | 0.141 | 0.0775 | 0.12 | 8 | |
F | 0.53 | 0.415 | 0.15 | 0.7775 | 0.237 | 0.1415 | 0.33 | 20 | |
F | 0.545 | 0.425 | 0.125 | 0.768 | 0.294 | 0.1495 | 0.26 | 16 | |
M | 0.475 | 0.37 | 0.125 | 0.5095 | 0.2165 | 0.1125 | 0.165 | 9 |
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On any given day i was responsible for perform code reviews. | |
Experience in developing a web product publisher to update existing products pages using advanced javascript and angularjs to successfully deliver to customers and to integrate documentation in the harbors. | |
Coordinated as head for the graduate level course mobile computing. | |
Computer graphics course projects d and graphic design of functional architecture by using etl. | |
Research existing web applications for internal users using angularjs concepts of components directives services promises templating scope dependency injection spring mvc hibernate for backend and jsp responses for interacting with the onboarding process of environment setup and maintenance. | |
Praised for passionate work ethic problem-solving skills and a premier google partner built to enable the running of more than million records of web sites ecom casual gaming site grab. | |
Established a product support team post launch that would periodically make updates and provide all the major bro |
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let u1: number | string | boolean = 1; | |
console.log(u1); | |
let u2 = 1 | 2; | |
console.log(u2); | |
// The left-hand side of an arithmetic operation must be of type 'any', 'number' or an enum type. | |
// let u3 = 'A' | 'B'; | |
interface A { |
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Math.floor(((function parseJwt(token) { | |
let base64Url = token.split('.')[1]; | |
let base64 = base64Url.replace('-', '+').replace('_', '/'); | |
return JSON.parse(window.atob(base64)); | |
})(window.localStorage.getItem('access_token')).exp - new Date() / 1000) / 60) |