It's time again to share your predictions for 2017. I did my homework and came with these 10 predictions. I invite you to post your predictions in the comment section, or write a blog about it. Ramon Chen's predictions are posted here, while you can read Tableau's prediction…

As data scientists plan and evolve their big data programs, it is time to evaluate the value of adding data in motion to the data lake. What’s the difference between data in motion and data at rest? We are all familiar with data at rest. This is the data we are most accustomed to working with. Data at rest is persistent data that is stored for some period of time on either disk or in memory like sales transaction records or account information. Data in motion, on the other hand, is…

The post 'Top programming languages that will be most popular in 2017' was originally posted on the HackerEarth blog.

Which is the most preferred programming language or the top programming languages to learn across the globe? How do we judge it and what should be the criteria?

'By most preferred language, we do…

Summary:  The data science press is so dominated by articles on AI and Deep Learning that it has led some folks to wonder whether Deep Learning has made traditional machine learning irrelevant.  Here we explore both sides of that argument.

On Quora the other day I saw a question from an aspiring data scientist that asked – since all the…

Here I list my most interesting contributions published on Data Science Central. My plan is to categorize and aggregate this content to produce a few self-published books. The material below will always be available for free (from this webpage), but the books won't, or if they are, they will be free for members only. So you might want to bookmark this page.   

I…

A popular phrase tossed around when we talk about statistical data is “there is correlation between variables”. However, many people wrongly consider this to be the equivalent of “there is causation between variables”. It’s important to explain the distinction: Correlation means that once we know how one variable changes we can make reasonable deductions about how other variables change There are several variants of correlation:

1. Positive…

People change jobs, get promoted and move home. Companies go out of business, expand and relocate.  Every one of these changes contributes to data decay. It’s been said that business databases degrade by around 30% per year, but why?

A report by IDG states that companies with effective data grow 35% faster year-on-year. However, for this to…

Enterprise AI insights from the AI Europe event in London

I attended…

The two situations discussed here also apply to marketing (not just advertising), and not just using social networks, but other channels such as Google. The insights provided here are based on careful data analysis, and applicable to websites and blogs with a decent amount of content, trying to build or maintain momentum. The problem discussed here is sometimes referred to as marketing mix optimization, with attribution modeling.

1. To Grow Subscriber or Member…

Guest blog by David Stephenson, Ph.D. David is a data science and big data analytics speaker and thought leader. For over 15 years, David has been delivering analytic and risk management tools that have guided $10+ billion in business decisions. Prior to returning to consulting, David led global analytics for eBay Classifieds Group, reaching 30 countries operating under a dozen consumer facing brands and spread over…

Guest blog by Ajit Jaokar. Ajit”s work spans research, entrepreneurship and academia relating to IoT, predictive analytics and Mobility. His current research focus is on applying data science algorithms to IoT applications. This includes Time series, sensor fusion and deep learning (mostly in R/Apache Spark). This research underpins his teaching at Oxford University (Data Science for IoT)…

Probably like most people, I tend to recognize data as a stream of values. Notice that I use the term values rather than numbers although in practice I guess that values are usually numerical. A data-logger gathering one type of data would result in data all of a particular type. Perhaps the concept of “big data” surrounds this preconception of data of type except that there are much larger amounts. Consider an element of value in symbolic terms, which I present below: there is an index such…

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

• Use data to drive decisions—and your career. Advance your knowledge through…

 I. Introduction

Contributed by Diego De Lazzari. He is currently in the NYC Data Science Academy 12-week full time Data Science Bootcamp program taking place between July 5th to September 23rd, 2016. This post is based on his second project - R Shiny (due on 4th week of the program). The R code can be found on GitHub  while the App is stored on…

Picture this.

You’re late for work and hungry too. You quickly enter a fast food joint and wait in the long queue for your turn. You wish there was a quicker service where your choice would pop up automatically on a system and you could shop based on your past purchase data.

Sounds good?

Well, it may not be at your nearest fast food joint right now, but companies like Amazon are tracking your past purchase data and…

Over the last five years or so, e-commerce has grown hugely around the world, as consumers take advantage of great online pricing, the convenience of shopping from anywhere at any time of the day or night, and the ability to discover a whole raft of products that otherwise would be beyond reach.

However, although it has been getting continually cheaper and easier for…

This is our selection of featured articles and resources posted since Monday.

Thursday News

• Beginners Guide to Regression Analysis and Plot Interpretations +
• Tutorial - foundations of machine learning…

About the book

You’re convinced that you want to enter into a data science career. You’ve done your research and even started to learn some of the skills needed. But how do you go from an data science enthusiast to a data scientist at your dream company?

What does a data science interview look like? What do recruiters really think of your resume? Where are the data science jobs? Can you improve your odds of getting an interview by employing a few clever…