mGBUfLn9

I was drawn to programming, science, technology and science fiction
ever since I was a little kid. I can't say it's because I wanted to
make the world a better place. Not really. I was simply drawn to it
because I was drawn to it. Writing programs was fun. Figuring out how
nature works was fascinating. Science fiction felt like a grand
adventure.

Then I started a software company and poured every ounce of energy
into it. It failed. That hurt, but that part is ok. I made a lot of
mistakes and learned from them. This experience made me much, much

dmmeteo

"""
Single Responsibility Principle
“…You had one job” — Loki to Skurge in Thor: Ragnarok
A class should have only one job. 
If a class has more than one responsibility, it becomes coupled. 
A change to one responsibility results to modification of the other responsibility.
"""

class Animal:
    def __init__(self, name: str):

jayliew

# Props to user brechmos for sharing the code here: https://www.raspberrypi.org/forums/viewtopic.php?t=55100

# Tested with the following barcode scanner
# macbook# ioreg -p IOUSB 
# <snip>
#   | +-o WIT 122-UFS V2.03@14200000  <class AppleUSBDevice, id 0x10000c3c4, registered, matched, active, busy 0 (6 ms), retain 14>

#        WIT 122-UFS V2.03:
#          Product ID: 0x1010
#          Vendor ID: 0x05fe  (CHIC TECHNOLOGY CORP)

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

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:

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

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

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
   

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)

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