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var mongoose = require('./db-connect'), | |
Schema = mongoose.Schema, | |
ObjectId = Schema.ObjectId, | |
uuid = require('node-uuid'), | |
Validator = require('validator').Validator, | |
val = new Validator(), | |
bcrypt = require('bcrypt'); | |
Validator.prototype.error = function(msg) { return false; }; |
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// Media Queries in Sass 3.2 | |
// | |
// These mixins make media queries a breeze with Sass. | |
// The media queries from mobile up until desktop all | |
// trigger at different points along the way | |
// | |
// And important point to remember is that and width | |
// over the portrait width is considered to be part of the | |
// landscape width. This allows us to capture widths of devices | |
// that might not fit the dimensions exactly. This means the break |
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/* | |
##Device = Desktops | |
##Screen = 1281px to higher resolution desktops | |
*/ | |
@media (min-width: 1281px) { | |
/* CSS */ | |
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// file: index.js | |
var _ = require("lodash"); | |
var express = require("express"); | |
var bodyParser = require("body-parser"); | |
var jwt = require('jsonwebtoken'); | |
var passport = require("passport"); | |
var passportJWT = require("passport-jwt"); |
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import * as tf from "@tensorflow/tfjs" | |
import "@tensorflow/tfjs-node" | |
import iris from "./iris.json" | |
import irisTesting from "./iris-testing.json" | |
// convert/setup our data | |
const trainingData = tf.tensor2d(iris.map(item => [ | |
item.sepal_length, item.sepal_width, item.petal_length, item.petal_width, | |
])) | |
const outputData = tf.tensor2d(iris.map(item => [ |
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const express = require('express'); | |
const fetch = require('node-fetch'); | |
const redis = require('redis'); | |
const PORT = process.env.PORT || 5000; | |
const REDIS_PORT = process.env.PORT || 6379; | |
const client = redis.createClient(REDIS_PORT); | |
const app = express(); |