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import requests as rq | |
import json | |
import collections | |
import time | |
API_KEY = 'APIKEY' | |
GROUP_ID = 'GROUPID' | |
def handle_event(event, event_dict): | |
event_dict[ event ] = {} |
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<!DOCTYPE html> | |
<html> | |
<head> | |
<title>d3.js with leaflet.js</title> | |
<link rel="stylesheet" href="http://cdn.leafletjs.com/leaflet-0.7/leaflet.css"/> | |
<script src="http://d3js.org/d3.v3.min.js"></script> | |
<script src="http://cdn.leafletjs.com/leaflet-0.7/leaflet.js"></script> | |
<script src="http://cdnjs.cloudflare.com/ajax/libs/lodash.js/2.4.1/lodash.js"></script> | |
<style> |
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<!DOCTYPE html> | |
<html> | |
<head> | |
<title>d3.js with leaflet.js</title> | |
<link rel="stylesheet" href="http://cdn.leafletjs.com/leaflet-0.7/leaflet.css"/> | |
<script src="http://d3js.org/d3.v3.min.js"></script> | |
<script src="http://cdn.leafletjs.com/leaflet-0.7/leaflet.js"></script> | |
<script src="http://cdnjs.cloudflare.com/ajax/libs/lodash.js/2.4.1/lodash.js"></script> | |
<style> |
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library(shiny) | |
library(ggplot2) | |
library(reshape2) | |
library(randomForest) | |
df = ChickWeight | |
n = nrow(df) | |
perfdf = data.frame(ntree=as.numeric(), mse_train=as.numeric(), mse_test=as.numeric()) | |
count = 0 |
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{ | |
"metadata": { | |
"name": "" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ | |
{ |
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# Neural PCA/Compression in R | |
In this document I will show a small experiment that shows how a neural network can be used as a pca-algorithm. It should also help explain how neural networks work and why neural networks can be such a powerful machine learning algorithm. | |
The code will be written in R and needs the following dependencies. | |
### Packages Used | |
```{r packages} | |
library(RSNNS) |
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{ | |
"metadata": { | |
"name": "", | |
"signature": "sha256:f2df6bbd409a5263ed5975f62791ba9a5f6c84469fdd4212a03e04b0f3bf051d" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ |
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{ | |
"metadata": { | |
"name": "" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ | |
{ |
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