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#!/usr/bin/env bash

# A basic Self Signed SSL Certificate utility
# by Andrea Giammarchi @WebReflection

# https://www.webreflection.co.uk/blog/2015/08/08/bringing-ssl-to-your-private-network

# # to make it executable and use it
# $ chmod +x certificate
# $ ./certificate # to read the how-to

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How to install cockpit on Debian/Ubuntu

$ git clone https://github.com/cockpit-project/cockpit.git
$ cd cockpit

Install latest nodejs

$ curl -sL https://deb.nodesource.com/setup_6.x | sudo -E bash -
$ sudo apt-get install -y nodejs

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Implementing the k-means jump method: Part Three

After implementing Sugar & James jump method and applying it straightforwardly to a few data sets, we're ready to throw it a few curveballs. This will demonstrate both its robustness and some necessary aspects of setting it up for success.

Again we need some functions we built in part one and part two. Feel free to skip this part if you don't need the review and you're not following along with a REPL. If you are following along in the REPL, here's the full Clojure source.

(def iris (i/to-matrix (incd/get-dataset :iris)))

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/*
      ____      _____
    /\__  \   /\  ___\
    \/__/\ \  \ \ \__/_
        \ \ \  \ \____ \
        _\_\ \  \/__/_\ \
      /\ _____\  /\ _____\
      \/______/  \/______/

   Copyright (C) 2011 Joerg Seebohn

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Implementing the k-means jump method: Part Two

After implementing Sugar & James' jump method and exploring its application to Fisher's iris data in Part One of this series, we're now ready to apply the jumps-in-distortions test to some other sample data sets. Pure Clojure source here.

Remember these functions from earlier? We'll be using them again.

(defn assoc-distortions
  "Given a number `transformation-power-y` and a seq of maps

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Implementing the k-means jump method: Part One

This paper:

Finding the number of clusters in a data set: An information theoretic approach

CATHERINE A. SUGAR AND GARETH M. JAMES

>Marshall School of Business, University of Southern California

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Introduction to Kafka

Kafka acts as a kind of write-ahead log (WAL) that records messages to a persistent store (disk) and allows subscribers to read and apply these changes to their own stores in a system appropriate time-frame.

Terminology:

• Producers send messages to brokers
• Consumers read messages from brokers
• Messages are sent to a topic

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#ThinkDSP 文件版本 0.10.0 ##目錄

• 前言
• 第一章 聲音與訊號 Sounds and signals
• 第二章 諧波 Harmonics
• 第三章 非週期訊號 Non-periodic signals
• 第四章 噪音 Noise
• 第五章 自相關 Autocorrelation

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The Anatomy of an Onyx Program

In this tutorial, we'll take an in-depth view of what's happening when you execute a simple Onyx program. All of the code can be found in the Onyx Starter repository if you'd like to follow along. The code uses the development environment with HornetQ and ZooKeeper running in memory, so you don't need additional dependencies to run the example for yourself on your machine.

The Workflow

At the core of the program is the workflow - the flow of data that we ingest, apply transformations to, and send to an output for storage. In this program, we're going to ingest some sentences from an input source, split the sentence into individual words, play with capitalization, and add a suffix. Finally, we'll send the transformed data to an output source.

Let's examine the workflow pictorially:

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Datomic pro with Postgresql Setup

Prep

• Get evaluation license key : http://my.datomic.com/eval/request
• Download pro version : http://downloads.datomic.com/pro.html

Setups

1. Dev mode setup