samklr

--------Spark Standalone---------
 
Prerequistes :
* Set JAVA_HOME env variable
* Configure ssh so master and workers can talk without pw
    - $ ssh-keygen -- enter
    - Copy the SSH Public Key (id_rsa.pub) to the root account on your target hosts.
        .ssh/id_rsa .ssh/id_rsa.pub
    - Add the SSH Public Key to the authorized_keys file on your target hosts.
        $ cat id_rsa.pub >> authorized_keys

samklr

package com.developerb.dropbot;

import com.developerb.dropbot.instrumentation.MethodInvocationTimingInterceptor;
import com.google.inject.AbstractModule;
import com.yammer.metrics.annotation.Timed;

import static com.google.inject.matcher.Matchers.annotatedWith;
import static com.google.inject.matcher.Matchers.any;

/**

samklr

sudo ufw allow proto tcp to any port 9200:9400
sudo ufw allow proto tcp to any port 54328
network.host: 127.0.0.1

samklr

#!/usr/bin/env bash

# update apt
sudo apt-get update

# install java
sudo apt-get install openjdk-7-jre-headless -y

# install elasticsearch
wget https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-1.5.0.deb

samklr

sudo apt-get -y install build-essential tcl8.5
wget http://download.redis.io/releases/redis-2.8.7.tar.gz
tar -xvf redis-2.8.7.tar.gz
cd redis-2.8.7
cd redis-2.8.7
sudo make install

samklr

import scala.collection.immutable.List

import spark.SparkContext._
import spark.streaming._
import spark.streaming.StreamingContext._
import spark.streaming.dstream._

object DataStream extends App {
  
  val reportHeader = """----------------------------------------------

samklr

#! /bin/bash

HOST_IP=10.11.31.7 ##Put your IP here
# or HOST_IP = ${/sbin/ifconfig eth0 | grep 'inet addr:' | cut -d: -f2 | awk '{ print $1}' }

#Start Zookeeper
docker run -d -p 2181:2181 -p 2888:2888 -p 3888:3888 garland/zookeeper

#Mesos Master
docker run --net="host" \

samklr

{
    "id": "/ctrlpkw/db",
    "apps": [
        {
            "id": "samklr/risk-metrix",
            "apps": [
                {
                    "id": "samklr/cassandra-seed",
                    "constraints": [
                        [

samklr

1. Feature Learning

• Learning Feature Representations with K-means by Adam Coates and Andrew Y. Ng
• The devil is in the details: an evaluation of recent feature encoding methods by Chatfield et. al.
• Emergence of Object-Selective Features in Unsupervised Feature Learning by Coates, Ng
• Scaling Learning Algorithms towards AI Benjio & LeCun

2. Deep Learning

• Dropout: A Simple Way to Prevent Neural Networks from Overfitting by Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever and Ruslan Salakhutdinov
• [Understanding the difficulty of training deep feedforward neural networks](http://jmlr.org/proceedings/papers/v9/glorot10a/gloro

samklr

#!/bin/zsh

#add in your meetup.com API key here
local key
key=

#add in your event ID here
local event
event=