herrfz

{
 "metadata": {
  "name": "k-means_clustering"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

herrfz

{
 "metadata": {
  "name": "svd_pca"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

herrfz

{
 "metadata": {
  "name": "clustering_example"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

herrfz

{
 "metadata": {
  "name": "soap_client"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

herrfz

package com.triagnosys.dms.tester;

import one_thousand_things;

public class TestCases extends TestCase {

  private static final String SOME_CONSTANTS;

	public void testGetSession() throws AxisFault {
		System.out.println("Testing DMS getSession");

herrfz

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

/*
 * MCrypt API available online:
 * http://linux.die.net/man/3/mcrypt
 */
#include <mcrypt.h>

herrfz

# Reuters-21578 dataset downloader and parser
#
# Author:  Eustache Diemert <[email protected]> 
# http://scikit-learn.org/stable/auto_examples/applications/plot_out_of_core_classification.html
#
# Modified by @herrfz, get pandas DataFrame from the orig SGML
# License: BSD 3 clause

from __future__ import print_function

herrfz

from sklearn.base import BaseEstimator, TransformerMixin

class Transformer(BaseEstimator, TransformerMixin):
    def __init__(self, fn):
        self.fn = fn

    def fit(self, X, y):
        return self

    def transform(self, X):

herrfz

{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

herrfz

Keybase proof

I hereby claim:

• I am herrfz on github.
• I am herrfz (https://keybase.io/herrfz) on keybase.
• I have a public key whose fingerprint is 76B8 3730 D93D 983E 887F 109E 9E04 2CAA 0416 640D

To claim this, I am signing this object: