sararob

'use strict';

// Dependencies
const gcloud = require('google-cloud', {
  projectId: 'sara-bigquery',
  keyfileName: 'keyfile.json'
});
const vision = gcloud.vision();
const fs = require('fs');
const async = require('async');

sararob

# Copyright 2021 Google LLC.
# SPDX-License-Identifier: Apache-2.0
import kfp
import json
import time
from google.cloud import bigquery
from google.cloud.exceptions import NotFound
from kfp.v2.google.client import AIPlatformClient

client = bigquery.Client()

sararob

/* 

This example shows how you can use your data structure as a basis for 
your Firebase security rules to implement role-based security. We store
each user by their Twitter uid, and use the following simplistic approach
for user roles:

0 - GUEST
10 - USER
20 - MODERATOR

sararob

// Get measurements for a new flower to generate a prediction
// The first argument is the data, and the second is the shape.
const inputData = tf.tensor2d([[4.8, 3.0, 1.4, 0.1]], [1, 4]);

// Get the highest confidence prediction from our model
const result = model.predict(inputData);
const winner = irisClasses[result.argMax().dataSync()[0]];

// Display the winner
console.log(winner);

sararob

'use strict';

const fs = require('fs');
const ndjson = require('ndjson');
const request = require('request');

fs.createReadStream('reddit-comments.json') // Newline delimited JSON file
  .pipe(ndjson.parse())
  .on('data', function(obj) {

sararob

#!/bin/bash

# SETUP
# 1) This requires having SoX (http://sox.sourceforge.net/) installed. On a Mac, you can do this with `brew install sox --with-flac`
# 2) You'll also need an API key for your Google Cloud Platform project: https://support.google.com/cloud/answer/6158862

# Create a request file with our JSON request in the current directory
FILENAME="request-"`date +"%s".json`
cat <<EOF > $FILENAME
{

sararob

# Enable Standard SQL to run this query
# More on BigQuery here: https://cloud.google.com/bigquery/docs/quickstarts
SELECT 
  REGEXP_REPLACE(starttime, '([0-9]{1,2})/([0-9]{1,2})/([0-9]{4})', '\\3-\\1-\\2') as starttime, 
  from_station_lat, 
  from_station_lng 
FROM `sara-bigquery.nyc_citibike.trips_*`
WHERE cast(bikeid as int64) = 17526 # This is the bike with the most trips (found from another query)
order by starttime

sararob

var App = Ember.Application.create({});

var Promise = Ember.RSVP.Promise;

// ADAPTER

App.ApplicationAdapter = DS.FirebaseAdapter.extend({
  firebase: new Firebase("https://<your-firebase-name>.firebaseio.com/")
});

sararob

await model.fit(
  xData, yData, {
    batchSize: batchSize,
    epochs: epochs
});

sararob

import * as tf from ‘@tensorflow/tfjs’;
const model = tf.sequential();
model.add(tf.layers.dense({inputShape: [4], units: 100}));
model.add(tf.layers.dense({units: 4}));
model.compile({loss: ‘categoricalCrossentropy’, optimizer: ‘sgd’});