# Featured Blog Posts – November 2016 Archive (85)

### Introduction to Number Theory: Fascinating Facts and Conjectures about Primes and Other Special Numbers

I discuss here off-the-beaten-path beautiful, even spectacular results from number theory: not just about prime numbers, but also about related problems such as integers that are sum of two squares. The connection between these numbers and prime numbers will appear later in this article. A few important unsolved mathematical conjectures are presented in a unified approach, and some new research material is also introduced, especially an attempt at generalizing and unifying concepts related…

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Added by Vincent Granville on November 16, 2016 at 10:00pm — No Comments

### Matrix Multiplication in Neural Networks

This post is the outcome of my studies in Neural Networks and a sketch for application of the Backpropagation algorithm. It's a binary classification task with N = 4 cases in a Neural Network with a single hidden layer. After the hidden layer and the output layer there are sigmoid activation functions. Different colors were used in the Matrices, same color as the Neural Network structure (bias, input, hidden, output) to make it easier to understand.…

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Added by Rubens Zimbres on November 16, 2016 at 11:00am — 4 Comments

### A Plethora of Data Set Repositories

These 19 'sets of data sets' cover free or public data from various industries, including small and large, structured and unstructured data sets. Hone your data science and machine learning skills on these data sets, or use them for testing algorithms  or for benchmarking.

19 data set repositories

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Added by Vincent Granville on November 16, 2016 at 8:30am — 1 Comment

### How to Ensure Your CRM Data Is Fit For Purpose

In this post we provide you with seven ways you can improve the quality of your data and ensure it is fit for purpose.

Constantly improving upon the quality of your data is essential to remain ahead of your competition. Failure to keep your data up to date will result in a 30% erosion in the value of your most…

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Added by Martin Doyle on November 16, 2016 at 2:30am — No Comments

### How to get the right data skills

In this post I want to talk about all of us finding our place and building our careers in data. And when I say “data”, I mean analytics, data science, business intelligence, and so on. In the previous post, I talked…

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Added by Olga on November 15, 2016 at 8:00pm — No Comments

### One-page R: a survival guide to data science with R

A Survival Guide to Data Science with R

These draft chapters weave together a collection of tools for the data scientist—tools that are all part of the R Statistical Software Suite.

Each…

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Added by Emmanuelle Rieuf on November 15, 2016 at 1:00pm — No Comments

### Machine Learning Poised to Impact Business Analytics

We may be years away from the “AI-enabled Coworker,” but the first implementations of machine-learning capabilities are finding their way into the everyday data-analysis tools used by businesses of all types. Cognitive assistance promises to reshape business processes, but only if app development and deployment tools are adapted to support machine learning.

While it has become fashionable to hypeAIas the next game-changing technology promising to have an impact greater than either…

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Added by Emmanuelle Rieuf on November 15, 2016 at 11:00am — No Comments

### What Can Modern Watson Do?

Summary:  IBM’s Watson as it exists today is as close as we’ve come to a single integrated platform for AI.  It contains all the capabilities for image and video, natural language speech and text input and output, and the most comprehensive knowledge recovery module yet combined together.  If you want to exploit the advances we’ve made in AI you need to understand where Watson is today and where it’s heading.

Recently we wrote about how the…

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Added by William Vorhies on November 15, 2016 at 8:47am — No Comments

### Visualizing Survey Data

This article comes from Data Revelations, a training, consulting, and development practice devoted to helping organizations understand, analyze, and share their data.

Here is a consolidation of the various blog posts Data Revelations has written on visualizing survey data:

General Survey…

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Added by Emmanuelle Rieuf on November 15, 2016 at 8:00am — No Comments

### Regression (LR and MLR) and differences, not for the Economy. Professional analyst should be able to answer these three questions.

To produce a regression analysis of inference that can be justified or trustworthy in the sense that helpful. The term in the statistical methods that generate a linear the best estimator is not bias (best linear unbiased estimator) abbreviated BLUE. Then there are some other things that are also important to note, in which the data to be processed, must meet certain requirements. In terms of statistical methods some terms or conditions of the so-called classical assumption test. Because…

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Added by Jeefri A. Moka on November 14, 2016 at 11:00am — 5 Comments

### White House Reports on Big Data, Algorithmic Systems, and Civil Rights

White House report on embedding civil rights principles into algorithms.

PREFACE........................4

• The Assumption: Big Data is Objective.......6
• Challenge 1: Inputs to an Algorithm...........7
• Challenge 2: The Design of Algorithmic…
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Added by Emmanuelle Rieuf on November 14, 2016 at 8:30am — No Comments

### Understanding machine learning #3: Confusion matrix - not all errors are equal

One of the most typical tasks in machine learning is classification tasks. It may seem that evaluating the effectiveness of such a model is easy. Let’s assume that we have a model which, based on historical data, calculates if a client will pay back credit obligations. We evaluate 100 bank customers and our model correctly guesses in 93 instances. That may appear to be  a good result – but is it really? Should we consider a model with 93% accuracy as adequate?

It depends. Today, we…

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Added by Algolytics on November 13, 2016 at 4:30am — No Comments

### Probabilistic Pentesting

Pentesting tools like Metasploit, Burp, ExploitPack, BeEF, etc. are used by security practitioners to identify possible vulnerability points and to assess compliance with security policies. Pentesting tools come with a library of known exploits that have to be configured or customized for your particular environment.  This configuration typically takes the form of a DSL or a set of fairly complex UIs to configure individual…

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Added by Arshak Navruzyan on November 12, 2016 at 1:00pm — No Comments

### Weekly Digest, November 14

Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week.

Announcements

• We’ve cracked the code to better BI. Get the intel on how to unlock your data’s true potential. View the…
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Added by Vincent Granville on November 12, 2016 at 11:00am — No Comments

### Hiring a Chief Data Scientist

A number of my mid-sized European clients recently have asked me to help them scope and recruit for the role of Chief Data Scientist (also scoped as ‘Head of Data Science’, ‘Lead Data Scientist’, ‘Head of Analytics’, etc.).

This lead data science role is typically opened by the client company for one of two…

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Added by David Stephenson on November 12, 2016 at 1:00am — No Comments

### 2015 Salary Survey of Business, Industry, and Government Statisticians

This article was posted by Patricia Hall and Varghese George on Amstatnews.

The ASA contacted the Statistical Consulting and Survey Center in the Augusta University Department of Biostatistics to help design and analyze the data for a survey of the association’s nonacademic members in the United States employed by business, industry, or government. Members were asked to report their annual base salary (in…

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Added by Emmanuelle Rieuf on November 11, 2016 at 6:00pm — No Comments

### Set the Machines free to learn

Guest blog by , Business Architecture / Strategy Director.

A decade ago straight through processing was a buzz word and speed to market was critical. The progress financial institutions have made in moving almost all aspects of their transaction foot print digital has left little to leverage on the transaction side.

In today’s day and time while most…

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Added by Vincent Granville on November 11, 2016 at 4:00pm — No Comments

### 10 Dataviz Tools To Enhance Data Science

This article on data visualization tools was written by Jessica Davis. She's passionate about the practical use of business intelligence, predictive analytics, and big data for smarter business and a better world.

Data visualizations can help business users understand analytics insights and actually see the reasons why certain recommendations make the most sense. Traditional business intelligence and analytics vendors, as well as newer market entrants, are offering data…

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Added by Emmanuelle Rieuf on November 10, 2016 at 9:00pm — No Comments

### Detecting In-App Purchase Fraud with Machine Learning

This article contains phrases taken from the machine learning and analysis world. Data scientists and algorithm engineers will feel more comfortable with reading it although it’s targeted at anyone who is interested in some deep data science learnings. It was written by Ella Gati. Ella is fascinated by machine learning and data science and is excited to be making big data valuable.

Hacking applications such as …

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Added by Emmanuelle Rieuf on November 10, 2016 at 4:30pm — No Comments

### 8 Essential Tools for Data Scientists

There is growing demand of data scientists in every organization. For growth of any business enterprise there is need to evaluate data in order to streamline the strategies and to keep a record. The skills of a data scientist boils down to the tools that they are able to use and are aware of. In this article we will talk of both the programming data science tools as well as ones which do not require much of coding to get started with.…

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Added by Joydeep Bhattacharya on November 10, 2016 at 6:54am — No Comments

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