benelsen

Map of all M2.5+ earthquakes of the last 24h.

Tectonic plate boundaries extracted from arcgis.com

d3noob

license: mit

dmuth

/*
 * This script goes through your Gmail Inbox and finds recent emails where you
 * were the last respondent. It applies a nice label to them, so you can
 * see them in Priority Inbox or do something else.
 *
 * To remove and ignore an email thread, just remove the unrespondedLabel and
 * apply the ignoreLabel.
 *
 * This is most effective when paired with a time-based script trigger.
 *

nikolak

# -*- coding: utf-8 -*-

# Form implementation generated from reading ui file 'design.ui'
#
# Created: Wed May 27 16:39:17 2015
#      by: PyQt4 UI code generator 4.11.3
#
# WARNING! All changes made in this file will be lost!

from PyQt4 import QtCore, QtGui

karpathy

"""
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)

bfontaine

1. Install Homebrew:

    ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
   

2. Download Java 6 on this page and install it

3. Install Gephi:

    brew cask install gephi
   

jdmaturen

Who pays when startup employees keep their equity?

JD Maturen, 2016/07/05, San Francisco, CA

As has been much discussed, stock options as used today are not a practical or reliable way of compensating employees of fast growing startups. With an often high strike price, a large tax burden on execution due to AMT, and a 90 day execution window after leaving the company many share options are left unexecuted.

There have been a variety of proposed modifications to how equity is distributed to address these issues for individual employees. However, there hasn't been much discussion of how these modifications will change overall ownership dynamics of startups. In this post we'll dive into the situation as it stands today where there is very near 100% equity loss when employees leave companies pre-exit and then we'll look at what would happen if there were instead a 0% loss rate.

What we'll see is that employees gain nearly 3-fold, while both founders and investors – particularly early investors – get dilute

jkleint

#!/usr/bin/env python
"""
Example of using Keras to implement a 1D convolutional neural network (CNN) for timeseries prediction.
"""

from __future__ import print_function, division

import numpy as np
from keras.layers import Convolution1D, Dense, MaxPooling1D, Flatten
from keras.models import Sequential

gbaman

# An example to get the remaining rate limit using the Github GraphQL API.

import requests

headers = {"Authorization": "Bearer YOUR API KEY"}


def run_query(query): # A simple function to use requests.post to make the API call. Note the json= section.
    request = requests.post('https://api.github.com/graphql', json={'query': query}, headers=headers)
    if request.status_code == 200:

ashokpant

#!/bin/bash

# install CUDA Toolkit v9.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb)
CUDA_REPO_PKG="cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb"
wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
sudo apt-get update
sudo apt-get -y install cuda-9-0