orenitamar

# Below are the dependencies required for installing the common combination of numpy, scipy, pandas and matplotlib 
# in an Alpine based Docker image.
FROM alpine:3.4
RUN echo "http://dl-8.alpinelinux.org/alpine/edge/community" >> /etc/apk/repositories
RUN apk --no-cache --update-cache add gcc gfortran python python-dev py-pip build-base wget freetype-dev libpng-dev openblas-dev
RUN ln -s /usr/include/locale.h /usr/include/xlocale.h
RUN pip install numpy scipy pandas matplotlib

jakechen

Introduction

This quick guide describes how to create a Jupyter Notebook in AWS EC2 then how to access it remotely using SSH tunneling. This method is preferred since you do not open any additional ports besides 22, requires little-to-no configuration, and is generally more straight-forward.

Pre-requisites

This current version assumes basic familiarity with cloud computing, AWS services, and Jupyter Notebook. Mostly because this version won't have images and won't dive too deep into each individual step.

Steps

Spin-up EC2 instance with "Deep Learning" AMI

1. Log into EC2 console and click "Launch Instance" button.
2. Inside "AWS Marketplace", select the "Deep Learning AMI" from AWS. I use this AMI because most of the stuff you'll need is installed already.

pratos

Install Zeppelin in Ubuntu systems

• First install Java, Scala and Spark in Ubuntu

  • Install Java

    sudo apt-add-repository ppa:webupd8team/java
    sudo apt-get update
    sudo apt-get install oracle-java8-installer
    

dimitardanailov

# Path to your oh-my-zsh installation.
export ZSH=/Users/dimitar.danailov/.oh-my-zsh

# Set name of the theme to load.
# Look in ~/.oh-my-zsh/themes/
# Optionally, if you set this to "random", it'll load a random theme each
# time that oh-my-zsh is loaded.
# ZSH_THEME="robbyrussell"
ZSH_THEME="agnoster"

wesleybliss

version: '2'
services:
    myapp:
        build: .
        container_name: "myapp"
        image: debian/latest
        environment:
            - NODE_ENV=development
            - FOO=bar
        volumes:

nzw0301

*2vec papers

1. act2vec, trace2vec, log2vec, model2vec https://link.springer.com/chapter/10.1007/978-3-319-98648-7_18
2. apk2vec https://arxiv.org/abs/1809.05693
3. app2vec http://paul.rutgers.edu/~qma/research/ma_app2vec.pdf
4. ast2vec https://arxiv.org/abs/2103.11614
5. attribute2vec https://arxiv.org/abs/2004.01375
6. author2vec http://dl.acm.org/citation.cfm?id=2889382
7. baller2vec https://arxiv.org/abs/2102.03291
8. bb2vec https://arxiv.org/abs/1809.09621

parijatmishra

#!/usr/bin/env python
# ddb_lsi_example: A sample program to show how to use Local Secondary Indexes
# in DynamoDB, using Python and boto3.
#
# Copyright 2016 Parijat Mishra
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0

erikbern

# Note – this is not a bash script (some of the steps require reboot)
# I named it .sh just so Github does correct syntax highlighting.
#
# This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5
#
# The CUDA part is mostly based on this excellent blog post:
# http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/

# Install various packages
sudo apt-get update

pgjones

from geventwebsocket.handler import WebSocketHandler
from gevent.pywsgi import WSGIServer
from flask import Flask, request, render_template_string
from flask_sockets import Sockets
import json

app = Flask(__name__)
sockets = Sockets(app)

template = """

xdamman

#!/bin/bash

# Bash script to install latest version of ffmpeg and its dependencies on Ubuntu 12.04 or 14.04
# Inspired from https://gist.github.com/faleev/3435377

# Remove any existing packages:
sudo apt-get -y remove ffmpeg x264 libav-tools libvpx-dev libx264-dev

# Get the dependencies (Ubuntu Server or headless users):
sudo apt-get update