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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 / 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": [
{
"cells": [
{
@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 / 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 / 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 / fritz_style_transfer_template.sh
Last active May 12, 2020 06:26
Train a Fritz Style Transfer model with a custom style image in 20 minutes. Create Core ML and TensorFlow Mobile versions for use in your app. More information at https://fritz.ai.
# A script to train an artistic style transfer model from a custom style image.
# A Google Colab going through the same steps can be found here:
# https://colab.research.google.com/drive/1nDkxLKBgZGFscGoF0tfyPMGqW03xITl0#scrollTo=V33xVH-CWUCs
# Note that this script will download and unzip 1GB of photos for training.
# Make sure you have the appropriate permissions to use any images.
# CHANGE ME BEFORE RUNNING
STYLE_IMAGE_URL='STYLE_IMAGE_URL'
# Install requirements
@jamesonthecrow
jamesonthecrow / inference_subreddit_suggester.swift
Last active November 11, 2018 03:37
Incorporate the subreddit suggester into your iOS app.
// Drag your subredditClassifier.mlmodel to the Xcode project navigator.
// Use the model with the following code.
import NaturalLanguage
let subredditPredictor = try NLModel(mlModel: subredditClassifier().model)
subredditPredictor.predictedLabel(for: "TIL you can use Core ML to suggest subreddits to users.")
@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))