Does Big Data mean Hadoop? Not really, however when one thinks of the term Big Data, the first thing that comes to mind is Hadoop along with heaps of unstructured data. An exceptional lure for data scientists having the opportunity to work with large amounts data to train their models and businesses getting knowledge previously never imagined. But has it lived up to the hype? In this article, we will look at a brief history of Hadoop and see how it stands today.

2015 Hype Cycle –…

Airbnb in New York City

Contributed by Jurgen de Jager. He takes the NYC Data Science Academy 12 week full time Data Science Bootcamp program from July 5th to September 22nd, 2016. This post is based on their first class project - the Exploratory Data Analysis Visualization Project, due on the 2nd week of the program. You can find the original article…

Contributed by David Richard Steinmetz. He takes the NYC Data Science Academy 12 week full time Data Science Bootcamp program from July 5th to September 22nd, 2016. This post is based on their first class project – the Exploratory Data Analysis Visualization Project, due on the…

When we talk about innovative services or products, many startups follow a smoother model of development. This allows them to minimize the…

Introduction 

According to Deloitte: by the “end of 2016 more than 80 of the world’s 100 largest enterprise software companies by revenues will have integrated cognitive technologies into their products”. Gartner also predicts that 40 percent of the new investment made by enterprises will be in predictive analytics by 2020. AI is moving fast into…

As the current wave of Artificial Intelligence apps continue to gain routine use, do we really trust them?

If not, here's a way of improving trust.  Write the apps in Executable English [1], so that they can explain their results and actions at the end user level.

What other approaches are there?

[1]  …

Here is our selection of featured articles and tutorials for today:

• A primer on universal function approximation with deep learning  (in Torch and R)
• A Primer in Adversarial Machine Learning - The Next Advance in AI, by…

We’re obviously in an age of unprecedented access to customer insights and information, but that doesn’t necessarily mean it’s easy to gather and leverage data. Businesses – small businesses, in particular – must be very strategic with the information they collect and how they go about procuring it.

Data collection and analysis takes time, so it would be a shame to focus on the wrong information.

Five Different Ways to Collect…

Beer is delicious but it is not one thing. If you disagree with the former part of the previous sentence please keep the latter in mind[1]. Think of sports, for instance. Many would agree with the blanket statement "sports are fun" but depending on what you have in mind two people can easily have opposite reactions to being presented the opportunity to play ping-pong. Sports are not one thing, music is not one thing, and neither is beer.

Presented with a finely crafted brew in…

McKinsey Global Consulting famously predicted a shortage of between 140,000 and 180,000 Data Scientists by 2018. That's about 15 months away. Will that prediction turn out to be correct? What do you think? How does it look?

Smart transportation uses information technology and artificial intelligence to efficiently manage and coordinate transportation systems. The application of smart transportation network allows the travelling population to have better knowledge of the traffic for better coordination. In addition, the use…

Credit : Seattle Metropolis October 2016. Click on picture to zoom 

DSC Resources

• Career: Training | …

Arthur C. Clarke famously stated that “any sufficiently advanced technology is indistinguishable from magic.” No current technology embodies this statement more than neural networks and deep learning. And like any good magic it not only dazzles and inspires but also puts fear into people’s hearts. This primer sheds some light on how neural networks work, hopefully adding to the wonder while reducing the fear.

One known property of artificial neural networks (ANNs) is that they are…

This reference is a part of a new series of DSC articles, offering selected tutorials on subjects such as deep learning, machine learning, data science, deep data science, artificial intelligence, Internet of Things, algorithms, and related topics. It is designed for the busy reader who does not have a lot of time digging into long lists of advanced publications.…

Summary:  What comes next after Deep Learning?  How do we get to Artificial General Intelligence?  Adversarial Machine Learning is an emerging space that points to that direction and shows that AGI is closer than we think.

Deep Learning, Convolutional Neural Nets (CNNs) have given us dramatic improvements in image, speech, and text recognition over the last two years.  They suffer from the flaw however that…

This is part of a new series of articles: once or twice a month, we post previous articles that were very popular when first published. These articles are at least 6 month old but no more than 12 month old. The previous digest in this series was posted here a while back. Below is our third edition.…

This article was written by Pallavi Poojary. 

In a world where 2.5 quintillion bytes of data is produced every day, a professional who can organize this humongous data to provide business solutions is indeed the hero! Much has been spoken about why Big Data is here to stay and why Big Data Analytics is the best career move. Building on what’s already been written and said, let’s discuss Data Science…

Update Sep. 2016: A model with less than a third of the error can be found here.

KIC 8462852 is a star that has been getting a fair amount of attention. It occasionally has unusual dips in brightness, according to Kepler telescope observations. Natural explanations for the…

This article was written by Richard Downes. Richard is a Specialist Recruiter / Headhunter in the areas of Analytics, Data Science and Artificial Intelligence / Machine Learning and NLP (Natural Language Processing). His work within Analytics covers Predictive Analytics, Consumer Insight / Shopper Insight, and Loyalty right the way through to Credit and Risk.…