This article was written by Roopam Upadhyay. Roopam is a seasoned professional of advanced analytics with more than a decade of experience in statistical modeling, data science, predictive analytics, optimization, & business consulting.
How do machines learn? They learn the same way as humans. Humans learn from experience and so do machines. For…Continue
Added by Emmanuelle Rieuf on March 15, 2017 at 12:00pm — No Comments
From NodeXLExcelAutomator, recently updated..
The graph represents a network of 3,210 Twitter users whose tweets in the requested range contained "data science" or #datascience", or who were replied to or mentioned in those tweets.
According to this source, the top influencers are:…Continue
Added by Emmanuelle Rieuf on March 15, 2017 at 12:00pm — No Comments
This infographic was posted by Robert Kelley on Dataiku.
Here at Dataiku, we frequently stress the importance of collaboration in building a successful data team. In short, successful data science and analytics are just as much about creativity as they are about crunching numbers, and creativity flourishes in a collaborative environment. One key to a collaborative environment is having a shared set of terms and…Continue
Added by Emmanuelle Rieuf on March 15, 2017 at 11:30am — No Comments
This article was posted by Clara Johnson.
Are you trying to find out how to access the dark web? Well, look no further, we have gone and done the research so we could show you…Continue
Added by Emmanuelle Rieuf on March 14, 2017 at 9:00am — No Comments
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.
23 Great Blogs Posted in the last 12…Continue
Added by Vincent Granville on March 14, 2017 at 7:41am — No Comments
We Didn’t Start The Big Data Fire
Unless you are hiding under a rock, you know that the Big Data fire is raging. Whole lot of people have contributed significantly to the advancement of Big Data over the years and quite a few are continuing to influence. I learn every day from these…Continue
Added by Ramesh Dontha on March 13, 2017 at 7:30am — No Comments
We have all read the punchlines – data scientist is the sexiest job, there’s not enough of them and the salaries are very high. The role has been sold so well that the number of data science courses and college programs are growing like crazy. After my previous blog post I have received questions from people asking how to become a data scientist – which courses are the best, what steps to take, what is the fastest way to land a data science job?
I tried to really think it…Continue
For Silicon Valley, the headline was sweet nectar: Google DeepMind, the world’s hottest artificial intelligence lab, embraces the blockchain, the endlessly fascinating idea at the heart of the bitcoin digital currency.
But the buzzwords bely the reality. The lab’s re-imagining of the blockchain has very little to do with AI—or the blockchain, for that matter. If you want AI crossed with the blockchain, try wrapping your head around Numerai, the world’s strangest hedge fund. To…Continue
Added by Robert on March 12, 2017 at 12:30pm — No Comments
Summary: Whether you are a startup person or data science-minded executive in a larger organization what logic can you apply to spot the most compelling opportunities for AI in your organization.
Added by William Vorhies on March 12, 2017 at 9:00am — No Comments
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.
Added by Vincent Granville on March 11, 2017 at 10:00am — No Comments
I am sometimes asked whether I am working on the stats, whether I am making progress on the stats, and what I do with all of the stats. People are also prone to hyperbole. I am told that I sure work on a lot of stats, I am always keeping myself busy doing stats, and I am the person to go to for stats. I suppose my real job is more mysterious than the one others imagine that I do. I first want to explain that for everyday people, the term “stats” or “statistics” often means historical…Continue
Added by Don Philip Faithful on March 11, 2017 at 10:00am — No Comments
Genevera I. Allen (left) is professor in the Departments of Statistics, and the Electrical and Computer Engineering, at Rice University. Corinne Cath (right) is a doctoral student at the Alan Turing Institute, the national institute for data science in UK. Below are extracts of recent interviews that are most relevant to…Continue
Added by Vincent Granville on March 10, 2017 at 3:30pm — No Comments
In this article, I present a few modern techniques that have been used in various business contexts, comparing performance with traditional methods. The advanced techniques in question are math-free, innovative, efficiently process large amounts of unstructured data, and are robust and scalable. Implementations in Python, R, Julia and Perl are provided, but here we focus on an Excel version that does not even require any Excel macros, coding, plug-ins, or anything other than the most basic…Continue
Data science today is a lot like the Wild West: there’s endless opportunity and excitement, but also a lot of chaos and confusion. If you’re new to data science and applied machine learning, evaluating a machine-learning model can seem pretty overwhelming. Now you have help. With this O’Reilly report, machine-learning expert Alice Zheng takes you through the model…Continue
Added by Emmanuelle Rieuf on March 10, 2017 at 8:00am — No Comments
I have seen the future! Of course, I seem to say that every other month (maybe that’s because the future keeps changing?), but this is a good one. The future is a collision between big data (and data science) and application development that will yield a world of “intelligent apps.” These “intelligent apps” combine customer, product and operational insights (uncovered with predictive and prescriptive analytics) with modern application development tools and user-centric design to create a…Continue
Added by Bill Schmarzo on March 9, 2017 at 10:30am — No Comments
Illegal, Unreported and Unregulated (IUU) fishing is becoming a major issue around the world . In general, IUU fishing is a broad term encapsulating many different scenarios (i.e. illegal: breaking laws, unreported: Not reporting catch, which may not be illegal, Unregulated: fishing in ways or places where there are no laws). For the purposes of this blog,…Continue
Added by Grant Humphries on March 9, 2017 at 2:30am — No Comments
What is data virtualization? Here’s an analogy using a concept that we can all relate to: a supermarket.
Picture the scene: Shopping list in one hand, shopping basket in the other, you’re ready to tackle your weekly shopping in your local supermarket. Your items range from fruit and vegetables to washing detergent, perhaps with some free-range eggs thrown in for good measure. Quite the eclectic mix, but you know that you’ll be able to find all you need under one…Continue
One of the best parts of my job is talking to a wide variety of customers across a wide variety of industries at a wide variety of different points on their big data journey. I’ve recently had several customer engagements where the client’s top business initiative is creating a Customer 360 View. Danger, Will Robinson!! I think the Customer 360 View business initiative is both dangerous and distracting; it is dangerous because it gives organizations a false goal to pursue, and it…Continue
Summary: IBM’s Watson now to do your taxes at H&R Block? This is a good opportunity to explore the differences between Question Answering Machines (Watson) and Expert Systems.
Added by William Vorhies on March 7, 2017 at 9:19am — No Comments
Imagine a world where your car not only drives itself, but also says intelligent things like these:
This would look like an impossibility…Continue
Added by Ronald van Loon on March 7, 2017 at 12:30am — No Comments