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rm -f tags
python setup.py clean
running clean
removing 'build/temp.macosx-10.7-x86_64-3.6' (and everything under it)
removing 'build'
Partial import of sklearn during the build process.
Will remove generated .c files
rm -rf dist
python setup.py build_ext -i
blas_opt_info:

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package org.apache.spark.sql.types

import xxx.Condition
import xxx.Department


class ConditionUDT extends UserDefinedType[Condition.Value] {
  override def sqlType: DataType = IntegerType

  override def serialize(obj: Condition.Value): Int = obj.id

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"""Information Retrieval metrics

Useful Resources:
http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt
http://www.nii.ac.jp/TechReports/05-014E.pdf
http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf
http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf
Learning to Rank for Information Retrieval (Tie-Yan Liu)
"""
import numpy as np

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fig, ax = plt.subplots(nrows=2, ncols=3)

perplexity = [[2, 10, 20],
              [30, 50, 100]]

iterations = [[1000, 1000, 1000],
            [1000, 1000, 1000]]

for ri, row in enumerate(ax):
    for ci, col in enumerate(row):

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from tempfile import NamedTemporaryFile
import base64

    
def inline_hist(data, figsize=(4, 4), **kwags):
    data = list(data)
    
    fig, ax = plt.subplots(1, 1, figsize=figsize, **kwags)
    for k,v in ax.spines.items():
        v.set_visible(False)

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import static java.lang.Math.sqrt;

public class S {

  public static void main(String[] args) {
    int[][] s = createSpiral(20);
    print(s);
  }

  private static int[][] createSpiral(int n) {

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import scipy.stats
import numpy as np
n = 200

s = scipy.stats.randint.rvs(0, n, size = 2)

X = scipy.stats.randint.rvs(0, n, size = s[0] * 2 + 1)
Y = scipy.stats.randint.rvs(0, n, size = s[1] * 2)

i = 1

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Internet Scale Services Checklist

A checklist for designing and developing internet scale services, inspired by James Hamilton's 2007 paper "On Desgining and Deploying Internet-Scale Services."

• http://mvdirona.com/jrh/talksandpapers/jamesrh_lisa.pdf

Basic tenets

• Does the design expect failures to happen regularly and handle them gracefully?
• Have we kept things as simple as possible?

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