A personal diary of DataFrame munging over the years.
Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)
""" | |
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
BSD License | |
""" | |
import numpy as np | |
# data I/O | |
data = open('input.txt', 'r').read() # should be simple plain text file | |
chars = list(set(data)) | |
data_size, vocab_size = len(data), len(chars) |
A personal diary of DataFrame munging over the years.
Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)
# Visualise a latex document git history | |
# loop through commits, create a PDF from your main file for each | |
# translate the pages of that PDF to a single image | |
# create GIF/mp4 from the folder of images created | |
# run within your local repository | |
# prerequisites: ImageMagick and FFmpeg | |
# create output folder |
# "Colorizing B/W Movies with Neural Nets", | |
# Network/Code Created by Ryan Dahl, hacked by samim.io to work with movies | |
# BACKGROUND: http://tinyclouds.org/colorize/ | |
# DEMO: https://www.youtube.com/watch?v=_MJU8VK2PI4 | |
# USAGE: | |
# 1. Download TensorFlow model from: http://tinyclouds.org/colorize/ | |
# 2. Use FFMPEG or such to extract frames from video. | |
# 3. Make sure your images are 224x224 pixels dimension. You can use imagemagicks "mogrify", here some useful commands: | |
# mogrify -resize 224x224 *.jpg | |
# mogrify -gravity center -background black -extent 224x224 *.jpg |