dsparks

doInstall <- TRUE
toInstall <- c("alphahull")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Generate some sample data:
myData <- data.frame(x = rnorm(500), y = rnorm(500))
# With a unit-circle hole in the center:
myData <- myData[sqrt(rowSums(myData^2)) > 1, ]
plot(myData)

mbostock

license: gpl-3.0
redirect: https://observablehq.com/@d3/d3-color-schemes

willurd

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

mblondel

"""Kernel K-means"""

# Author: Mathieu Blondel <mathieu@mblondel.org>
# License: BSD 3 clause

import numpy as np

from sklearn.base import BaseEstimator, ClusterMixin
from sklearn.metrics.pairwise import pairwise_kernels
from sklearn.utils import check_random_state

33eyes

Commit jupyter notebooks code to git and keep output locally

1. Add a filter to git config by running the following command in bash inside the repo:

git config filter.strip-notebook-output.clean 'jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to=notebook --stdin --stdout --log-level=ERROR'  

2. Create a .gitattributes file inside the directory with the notebooks

3. Add the following to that file: