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jamesonthecrow / calles_update
Created December 3, 2014 20:30
{
"metadata": {
"name": "Trip Tables"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
@jamesonthecrow
jamesonthecrow / RouterChecks
Last active August 29, 2015 14:12
Calles Router Figures
{
"metadata": {
"name": "RouterChecks"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
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@jamesonthecrow
jamesonthecrow / index.html
Last active December 27, 2015 23:19
<!DOCTYPE html>
<meta charset="utf-8">
<style>
body{
font-family: sans-serif;
}
#container {
width: 1000px;
margin: 50px auto;
@jamesonthecrow
jamesonthecrow / index.html
Last active December 26, 2016 08:00
A visualization to explore timeseries of MIT wifi network data.
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>MIT Wifi - Timeseries</title>
<link rel="stylesheet" href="styles.css">
<style>
@jamesonthecrow
jamesonthecrow / turicreate_not_hotdog_medium_post.py
Last active February 15, 2018 00:35
Code snippets for the Medium post on building Not Hotdog with Turi Create
import requests
import shutil
import os
def download_images(url_filename, out_directory, max_urls=None):
"""Download images from a file containing URLS.
The URL file must contain a single URL per line.
Args:
@jamesonthecrow
jamesonthecrow / timePredict.swift
Last active February 28, 2018 14:04
Benchmarking neural networks in Swift.
struct Debug {
struct Timer {
let start = DispatchTime.now().uptimeNanoseconds
func end() -> Double {
let end = DispatchTime.now().uptimeNanoseconds
let diff = Double(end — start) / 1_000_000_000
return diff
}
}
}
@jamesonthecrow
jamesonthecrow / time_func.py
Last active February 28, 2018 14:05
Benchmarking neural networks in python
def time_func(function, func_args=None, func_kwargs=None):
"""Time a single call of a function.
Args:
function (function): a function object to time
func_args (list, optional): the args for the function
func_kwargs (dict, optional): the kwargs for the function
Returns:
double: duration of the function call in sections
"""
args = func_args or []
@jamesonthecrow
jamesonthecrow / subreddit_suggester_preprocess_data.py
Created November 11, 2018 03:34
Preprocess data for the subreddit suggester.
import pandas
import re
import json
# Use pandas and regex to clean up the post titles.
df = pandas.DataFrame(posts, columns=['subreddit', 'title'])
# Remove any [tag] markers in a post title
df.title = df.title.apply(lambda x: re.sub(r'\[.*\]', '', x))
# Remove all other punctuation except spaces
df.title = df.title.apply(lambda x: re.sub(r'\W(?<![ ])', '', x))
@jamesonthecrow
jamesonthecrow / subreddit_suggester_reddit_scraper.py
Created November 11, 2018 03:34
Scrape data for the subreddit suggester.
import requests
import json
def get_listing(subreddit, sort='top', after=None, limit=25):
# Set the user agent on the request so we don't get rate limited
headers = {'User-agent': 'Subreddit Title Bot'}
url_fmt = 'https://www.reddit.com/r/{subreddit}/{sort}.json'
url = url_fmt.format(subreddit=subreddit, sort=sort)
params = {'after': after, 'limit': limit, 't': 'year'}
response = requests.get(url, params=params, headers=headers)
@jamesonthecrow
jamesonthecrow / subreddit_suggester_test_custom.py
Last active November 11, 2018 03:35
Test the subreddit suggester on some custom titles.
# Test the model on some titles I wrote with specific subreddits in mind.
sample_titles = [
'Saw this good boy at the park today.',
'Latest NIPS submission from OpenAI',
'TIL you can use Core ML to suggest subreddits to users',
'I made a tutorial using CreateML AMA',
'Westworld and Game of Thrones coming to netflix',
'We park in driveways, but drive on parkways',
'From the top of Mt. Fuji, Japan',
"What's the first thing you do every morning?",