eliasah

create conda env

conda create --name keras
source activate keras

installing utilities

conda install python=3.5 numpy scikit-learn=0.18.1 jupyter matplotlib pip
conda install pandas h5py pillow lxml

eliasah

To correctly work with Anaconda on Powershell :

• Run the anaconda command :

C:\Users\elias\Anaconda3> cmd C:\Users\elias\Anaconda3\envs\py35\Scripts\activate.bat C:\Users\elias\Anaconda3\envs\py35\Scripts\activate.bat
Microsoft Windows [Version 10.0.14393]
(c) 2016 Microsoft Corporation. All rights reserved.

• Activate your env :

eliasah

import pandas as pd
import numpy as np
import scipy
import scipy.stats as sts
import random

import pyspark
import pyspark.sql.types as stypes
import pyspark.sql.functions as sfunctions

eliasah

-server
-Xms2048m
-Xmx2048m
-XX:NewSize=512m
-XX:MaxNewSize=512m
-XX:PermSize=512m
-XX:MaxPermSize=512m
-XX:+UseParNewGC
-XX:ParallelGCThreads=4
-XX:MaxTenuringThreshold=1

eliasah

#!/bin/bash 

# usage dupes location

if [ "$#" -ne 2 ]; then 
    echo "Usage : dupes location type (pdf,gz)"
    exit
fi

LOCATION=$(readlink -f $1)

eliasah

#!/bin/bash

sudo apt-key adv --keyserver keyserver.ubuntu.com --recv E56151BF
DISTRO=$(lsb_release -is | tr '[:upper:]' '[:lower:]')
CODENAME=$(lsb_release -cs)
echo "deb http://repos.mesosphere.io/${DISTRO} ${CODENAME} main" | sudo tee /etc/apt/sources.list.d/mesosphere.list

sudo apt-get -y update
sudo apt-get -y install mesos marathon

eliasah

Hello, I am using linear SVM to train my model and generate a line through my data. However my model always predicts 1 for all the feature examples. Here is my code:

print data_rdd.take(5) [LabeledPoint(1.0, [1.9643,4.5957]), LabeledPoint(1.0, [2.2753,3.8589]), LabeledPoint(1.0, [2.9781,4.5651]), LabeledPoint(1.0, [2.932,3.5519]), LabeledPoint(1.0, [3.5772,2.856])]

---

from pyspark.mllib.classification import SVMWithSGD from pyspark.mllib.linalg import Vectors from sklearn.svm import SVC

eliasah

#!/bin/bash

sudo yum -y install make
sudo yum -y update
sudo yum -y install gcc gcc-c++ git
git clone https://github.com/dmlc/xgboost --recursive
cd xgboost
make -j4
cd python-package; sudo python setup.py install
export PYTHONPATH=~/xgboost/python-package

eliasah

import numpy as np
import tensorflow as tf
import os
from tensorflow.python.platform import gfile
import os.path
import re
import sys
import tarfile
from subprocess import Popen, PIPE, STDOUT
def run(cmd):

eliasah

import org.apache.http.client.methods.HttpGet
import org.apache.http.impl.client.{BasicResponseHandler, HttpClientBuilder}
import org.apache.spark.mllib.fpm.PrefixSpan

// sequence database
val sequenceDatabase = {
  val url = "http://www.philippe-fournier-viger.com/spmf/datasets/SIGN.txt"
  val client = HttpClientBuilder.create().build()
  val request = new HttpGet(url)
  val response = client.execute(request)