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.

Announcement…

Written by Henry Hinnefeld, Lead Data Scientist at Civis Analytics

Mario Kart was a staple of my childhood — my friends and I would spend hours after school as Mario, Luigi, and other characters from the Nintendo universe racing around cartoonish tracks and lobbing pixelated bananas at each other. One thing that always vexed our little group of would-be…

This article was posted by Sunil Ray. Sunil is a Business Analytics and Intelligence professional with deep experience in the Indian Insurance industry.

Introduction

Linear and Logistic regressions are usually the first algorithms people learn in predictive modeling. Due to their popularity, a lot of analysts even end up thinking that they are the only form of regressions. The ones who are slightly more involved think that they…

Data has become a cargo cult. Collect more data, calculate more metrics, hire more analysts, let them figure out what this is all for – and you’re considered to be data driven. I've had it up to here while consulting startups over the past three years and helping them to define business…

This article was posted by Roberto Rösler on his personal blog about R and data mining. Roberto is a data scientist working at a major telecommunication company in Germany.…

Not quite ready for world domination! 'Suicidal' security robot drowns itself in a fountain

Alas, it seems we've got a few more years before the robots take over.

A security robot created by the company Knightscope was patrolling an office complex in Washington D.C. when it rolled into a fountain…

Sales Forecasting: Science or Instinct?

Recently, we had talked about marketing automation, a digital transformation in the field that involved both artificial intelligence and machine learning. Even Natural Language Processing (NLP) has come a long way, enough to change the content marketing game. But while marketing has shifted to a digital…

Bill is the Editorial Director for Data Science Central, and President and Chief Data Scientist at Data-Magnum, providing predictive analytics and big data infrastructure projects as a service. Bill has been an active commercial predictive modeler since 2001.

Bill Vorhies

In this…

Summary:  There is a great hue and cry about the danger of bias in our predictive models when applied to high significance events like who gets a loan, insurance, a good school assignment, or bail.  It’s not as simple as it seems and here we try to take a more nuanced look.  The result is not as threatening as many headlines make it seem.

 …

In a blog from three months ago, I wrote on "kind of" big data in R. The "kind of" was meant as a caveat that data size in R is limited by RAM. I also mentioned the potential of working with relational data stores for even larger data, and made a vague proposal to…

Introduction

Did you know that you can write R and Python code within your T-SQL statements? Machine Learning Services   in SQLServer eliminates the need for data movement. Instead of transferring large and sensitive data over the network or losing accuracy with sample csv files, you can have your R/Python code execute within your database. Easily deploy your R/Python code with SQL stored procedures making them accessible in your…

Deep Learning is an algorithm which has no theoretical limitations of what it can learn; the more data you give and the more computational time you give, the better it is – Sir Geoffrey Hinton (Google).

The true challenge to Artificial Intelligence is to prove and  solve the tasks that are easy for human to perform but hard to describe formally. Problems that we solve intuitively, that feel automatic, like…

This article was written by Adam Geitgey. Adam is interested in computers and machine learning. He likes to write about it. 

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.

• Transform Data Into Something Meaningful. …

Full title: Applied Stochastic Processes, Chaos Modeling, and Probabilistic Properties of Numeration Systems. An alternative title is Organized Chaos. Published June 2, 2018. Author: Vincent Granville, PhD. (104 pages, 16 chapters.)

This book is intended for professionals in data science, computer science, operations research, statistics, machine learning, big data, and mathematics. In 100 pages, it…

In the “Ecology of Metrics,” I wrote about “alignment” being a type of metric; alignment can measure the extent to which an organization’s supply or capacity is matched against the demands or needs of the market.  For instance, in a call centre, it would be highly desirable to have agents available to respond to calls at “precisely” the same time that clients are making calls.  If alignment is off even by only 15 to 30 seconds, impatient clients might hang up and never call again.  Similarly…

In a previous blog I wrote about 6 potential applications of time series data. To recap, they are the following:

1. Trend analysis
2. Outlier/anomaly detection
3. Examining shocks/unexpected variation
4. Association analysis
5. Forecasting
6. Predictive analytics

Here I am focusing on outlier…

This article was written by Jean Francois Puget. 

What programming language should one learn to get a machine learning or data science job?  That's the silver bullet question.  It is debated in many forums.  I could provide here my own answer to it and explain why, but I'd rather look at some…