| // Processing 3.0x code to demonstrate seamless loop of 1D noise | |
| // Inspired by, and created in support of: | |
| // "Drawing from noise, and then making animated loopy GIFs from there" by Etienne Jacob (@n_disorder) | |
| // https://necessarydisorder.wordpress.com/2017/11/15/drawing-from-noise-and-then-making-animated-loopy-gifs-from-there/ | |
| // Note: this program has no dependencies, and does not require SimplexNoise. | |
| // Demo GIF: https://media.giphy.com/media/xUOxeU2ELSPeTbevle/giphy.gif or http://gph.is/2Ah5kqG | |
| PGraphics offscreenImg; | |
| float myScale = 0.01; | |
| float radius = 100.0; |
| #!/usr/bin/python | |
| # GoogleMapDownloader.py | |
| # Created by Hayden Eskriett [http://eskriett.com] | |
| # | |
| # A script which when given a longitude, latitude and zoom level downloads a | |
| # high resolution google map | |
| # Find the associated blog post at: http://blog.eskriett.com/2013/07/19/downloading-google-maps/ | |
| import urllib.request | |
| from PIL import Image |
| '''This script goes along the blog post | |
| "Building powerful image classification models using very little data" | |
| from blog.keras.io. | |
| It uses data that can be downloaded at: | |
| https://www.kaggle.com/c/dogs-vs-cats/data | |
| In our setup, we: | |
| - created a data/ folder | |
| - created train/ and validation/ subfolders inside data/ | |
| - created cats/ and dogs/ subfolders inside train/ and validation/ | |
| - put the cat pictures index 0-999 in data/train/cats |
This document: https://goo.gl/AqGoE8
By far the most annoying part of getting started with messing with ML is installing researcher-made code and turning it into something fun to play with.
Before doing any of these, please install Miniconda. If you don't have it installed already, here's how:
For OSX, this is:
This document: https://goo.gl/AqGoE8
By far the most annoying part of getting started with messing with ML is installing researcher-made code and turning it into something fun to play with.
Before doing any of these, please install Miniconda. If you don't have it installed already, here's how:
For OSX, this is: