Featured Blog Posts – July 2015 Archive (65)

How to Ensure a High Data IQ Score

By Jeff Brown, Product Manager at Infogix, Inc

It’s hard to imagine a doctor being content with a partial diagnosis of a patient’s health. Similarly, it can be difficult to understand why companies would only invest partially in understanding the health of their data. In an organization,…


Added by Andrei Macsin on July 31, 2015 at 7:30pm — No Comments

Stop Hiring Data Scientists if you’re not ready for Data Science

Guest blog post. Originally posted here

Greta Roberts, CEO, Talent Analytics, Corp.

I had yet another call today with a brilliant data scientist working inside of a Human Resources Department of a major business. This HR data scientist has both a strong analytics and predictive analytics background. She has a Bachelor’s Degree in…


Added by Andrei Macsin on July 31, 2015 at 9:21am — No Comments

17 Useful Data Science and ML Resources

Use our search engine to find popular articles and tutorials on R, Python, Excel, Hadoop, Visualization, Machine Learning, NoSQL and other data science related topics: 

Selected Authors…


Added by Andrei Macsin on July 31, 2015 at 8:30am — No Comments

Aster and Generalized Linear Model Functionality

Summary:  The generalized linear model (GLM) extends from the general linear model to accommodate dependent variables that are not normally distributed.  GLM is a methodology for modeling relationships between variables.

Use Cases:  

  -  Insurance and Loss Prediction…


Added by John Thuma on July 30, 2015 at 1:00pm — No Comments

Dummies for Data Science - A Reading List

There are two new books in the "... For Dummies" series that are targeted to our profession: "Data Science For Dummies" by Lillian Pierson, and "Data Mining for Dummies" by …


Added by Kirk Borne on July 30, 2015 at 4:30am — 2 Comments

Evolution of Deep learning models

Scope and approach

No taxonomy of Deep learning models exists. And I do not attempt to create one here either. Instead, I explore the evolution of Deep learning models by loosely classifying them into Classical Deep learning models andEmerging Deep Learning models. This is not an exact classification. Also, we embark on this exercise keeping our goal in mind i.e. the application of Deep learning…


Added by ajit jaokar on July 29, 2015 at 11:30am — No Comments

National Institute of Standards and Technology Takes on Big Data

Summary:  NIST weighs in on Big Data technology, standards, use cases, and a surprising variety of valuable documentation.

You can bet that the folks at DARPA and our other Federal forward thinkers had their eye on Big Data pretty much from its inception in about 2007.  Say what you will about the Fed but those research dollars gave us the Internet, super computing, and a whole…


Added by William Vorhies on July 28, 2015 at 3:04pm — 3 Comments

24 Data Science, R, Python, Excel, and Machine Learning Cheat Sheets

Here's a good starting point. You can find many additional references here (Python, Excel, Spark, R, Deep Learning, AI, SQL, NoSQL, Graph Databses, Visualization, etc.) as well as here, here, and…


Added by Tim Matteson on July 28, 2015 at 12:00pm — 4 Comments

Hadley Wickham, the Man Who Revolutionized R

Wickham earned his renown as the preeminent developer of packages for R, a programming language developed for data analysis. Packages are programming tools that simplify the code necessary to complete common tasks such as aggregating and plotting data. He has helped millions of people become more efficient at their jobs -- something for which they are often, and…


Added by Tim Matteson on July 28, 2015 at 11:00am — No Comments

Deep Learning vs Machine Learning vs Pattern Recognition

I think I have a pretty good grasp on the meaning and scope of 'Machine Learning' but less so on the emerging field of 'Deep Learning'.  Tomasz Malisiewicz has both the background and perspective to put these terms in context for us and I enjoyed his clear explanation.  You can see it here:…


Added by William Vorhies on July 28, 2015 at 7:31am — 3 Comments

10 Machine Learning Terms Explained in Simple English

If you’re relatively new to Machine Learning and it’s applications, you’ll more than likely have come across some pretty technical terms that are often difficult for the novice mathematician/scientist to get their head around.

Following on from a previous blog, (10 Common NLP Terms Explained for the Text Analysis Novice), we decided to put together a list of 10 Machine…


Added by Mike Waldron on July 28, 2015 at 6:30am — 1 Comment

Text Analytics Suffers a Setback from Facebook

If you do text analytics and sentiment analysis then you've likely come to expect the open and free APIs from all the major social media sources as something that won't go away.  But about 90 days ago Facebook withdrew open access to its Facebook posts data stream and made it available only to a select list of developers that support Facebook.  This is quite a blow to the larger social media monitoring industry but may be just the first of many instances where the big social media sites…


Added by William Vorhies on July 27, 2015 at 3:01pm — No Comments

The Beginner's Guide to Amazon Web Services - Infographic

This guest blog comes to us from Samantha R. at Udemy and is a cool infographic about AWS.  The original can be viewed here…


Added by William Vorhies on July 27, 2015 at 9:30am — No Comments

Data Science and Technology Monthly - July 2015

Hello and Welcome!

This is my attempt to start cataloging all the interesting articles, industry reports, whitepapers, and news that I read every month, related to technology and data science. There are tons of material published everyday. Of course, I can't read them all because I am human! But I want to share everything that I found to be…


Added by Srividya Kannan Ramachandran on July 27, 2015 at 7:33am — 1 Comment

Data: The Key to B2B Marketing Lead Generation


Most B2B marketers are swimming in a sea of data. After all, “data is essential in marketing,” and “data drives results.” However, as you are taking this swim, you may also feel a bit like you are drowning in too much data. Rest assured - with a little structuring and integration, you will soon be safely navigating your way to shore, data insights in hand and the winning formula on how to sell more to your B2B buyers.

In fact, most B2B marketers…


Added by Larisa Bedgood on July 27, 2015 at 7:21am — No Comments

Overcoming Aspects of Social Disablement in Data

When the performance of an employee is evaluated, ideally there are no externalities to complicate the analysis. If the employee has a computer that is constantly freezing up - or the servers in the company frequently operate slowly - the employee's performance data will reflect the functionality and effectiveness of these systems. If the company occupies a highly competitive market, declining sales data is attributable at least in part to competition rather than the behaviours of employees.…


Added by Don Philip Faithful on July 25, 2015 at 5:44am — No Comments

Analytical Data Marts – data analyst’s indispensable tool

Information about provided services, customers and transactions can be stored in different database systems and data warehouses, depending on the way in which a company operates.

Due to such arrangements, even the simplest analyses or report may require significant expenditures of time, as well as in-depth knowledge about database systems and their availability.

For an analyst this situation is frequently the source of difficulties – lack of required…


Added by Algolytics on July 24, 2015 at 6:00pm — No Comments

The Big 'Big Data' Question: Hadoop or Spark?

One question I get asked a lot by my clients recently is: Should we go for Hadoop or Spark as our big data framework? Spark has overtaken Hadoop as the most active open source Big Data project. While they are not directly comparable products, they both have many of the same uses.

Source for picture: …


Added by Bernard Marr on July 24, 2015 at 11:00am — 5 Comments

The Big Data Contrarians: The Agora for Big Data dialogue on LinkedIn

"In fact men will fight for a superstition quite as quickly as for a living truth - often more so, since a superstition is so intangible you cannot get at it to refute it, but truth is a point of view, and so is changeable."


On the 1st of July, I decided to set up a professional group on LinkedIn in order to create a hype free…


Added by Martyn Jones on July 23, 2015 at 5:18pm — No Comments

Analytics and Big Data: The Skeptics Versus the Enthusiasts

I recently started reading Gary's blogs and thought we shared both a point of view (a higher level what's good for the business POV) and that little voice in the back of our heads that's always asking - is that really true?  Hope you enjoy this one.  Many of Gary's current blogs appear here.…


Added by William Vorhies on July 23, 2015 at 8:30am — No Comments

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