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…

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…

Data Science has made great strides in the last couple of decades and has promise to improve the lives of everyone. Like any technology some may view these developments to be not such a great blessing after all. I felt taking a few moments to reflect on the long-term consequences might be of some value.

I came across this post after a lapse of a season and realized…

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…

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 …

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…

The full version is always published Monday. Starred articles are new additions or updated content, posted between Thursday and Sunday. The picture of the week is from the contribution marked with a +, where you will find the details.

Featured

• Evolution of Deep learning…

This guide addresses the following questions, with sample source code:

• How to load data file(s)?
• How to convert a variable to different data type?
• How to transpose a table?
• How to sort Data?
• How to create plots (Histogram, Scatter, Box Plot)?
• How to generate frequency tables?
• How to do sampling of Data set?
• How to remove duplicate values of a variable?
• How to group variables to calculate count, average,…

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…

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…

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…

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:…

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…

By web spam, we mean any technique - using Botnets or other forms of fake clicks - to manipulate web traffic statistics, to make your articles appear at the top on search results pages or other list of top articles. Web spam techniques exploit weaknesses in traffic monitoring algorithms.  In the most simplest form, a rogue author will crawl his articles dozens or hundreds of times a day, hoping to be featured in the list of most popular articles.…

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…

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

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…

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…

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.…