dylanjcastillo

"""
1. Setup a Twitter Developer account and create new App, get its consumer key and consumer secret and replace them below
2. Replace TWEETS_DB, QUERY, and LANGUAGE values
3. Install required packages: `pip install tweepy schedule`
4. Run process using `python tweets_to_db.py`
"""

import tweepy
import sqlite3
import datetime

alfredfrancis

cloudpickle
tensorflow
spacy
numpy
sklearn

urigoren

from keras.layers import Dense, Dropout, LSTM, Embedding
from keras.preprocessing.sequence import pad_sequences
from keras.models import Sequential
import pandas as pd
import numpy as np

input_file = 'input.csv'

def load_data(test_split = 0.2):
    print ('Loading data...')

nateinaction

/*
 * This is a version of Facebook's React Conditional Rendering
 * example modified to support firebase authentication.
 * https://facebook.github.io/react/docs/conditional-rendering.html
 */

import React, { Component, PropTypes } from 'react';
import * as firebase from 'firebase';

function UserAvatar(props) {

EncodeTS

VGG-Face model for Keras

This is the Keras model of VGG-Face.

It has been obtained through the following method:

• vgg-face-keras:directly convert the vgg-face matconvnet model to keras model
• vgg-face-keras-fc:first convert vgg-face caffe model to mxnet model,and then convert it to keras model

Details about the network architecture can be found in the following paper:

spandanb

#Original Author https://raw.githubusercontent.com/kgoedecke/python-ecs-example/master/python_ecs_example/deployment.py
import boto3
import pprint
import os

# Credentials & Region
access_key = os.environ["AWS_ACCESS_KEY_ID"]
secret_key = os.environ["AWS_SECRET_ACCESS_KEY"]
region = "us-east-1"

hnykda

import pandas as pd  
from random import random

flow = (list(range(1,10,1)) + list(range(10,1,-1)))*100
pdata = pd.DataFrame({"a":flow, "b":flow})  
pdata.b = pdata.b.shift(9)  
data = pdata.iloc[10:] * random()  # some noise  

import numpy as np

mattupstate

from dictalchemy import make_class_dictable
from flask import Flask, request, jsonify, json
from flask_sqlalchemy import SQLAlchemy
from jsonpatch import JsonPatch, JsonPatchException

app = Flask(__name__)
app.debug = True
db = SQLAlchemy(app)
make_class_dictable(db.Model)

dennisdegryse

<?php

class Router {
	private $_defaultParameters;
	
	public Router($defaultParameters) {
		$this->_defaultParameters = $defaultParameters;
	}
	
	public function route($uri) {

guyc

import wiringpi
import time

# 1M external pull-up resistor
# 1) set pin low and to output to discharge
# 2) make the pin an input without the internal pull-up on
# 3) read input and see how long it takes to go high

# ref: https://github.com/WiringPi/WiringPi-Python
# pins: https://projects.drogon.net/raspberry-pi/wiringpi/pins/