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Great Sunday Reading

Here is our selection of featured articles and resources posted in the last few days:

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Added by Vincent Granville on February 18, 2018 at 12:06pm — No Comments

Generalized Coefficient of Correlation for Non-Linear Relationships

What is the best correlation coefficient R(XY) to measure non-linear dependencies between two variables X and Y? Let's say that you want to assess weather there is a linear or quadratic relationship between X and Y.  How can you do it?…

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Added by Vincent Granville on February 15, 2018 at 6:30pm — No Comments

Supervised learning in disguise: the truth about unsupervised learning

One of the first lessons you’ll receive in machine learning is that there are two broad categories: supervised and unsupervised learning. Supervised learning is usually explained as the one to which you provide the correct answers, training data, and the machine learns the patterns to apply to new data. Unsupervised learning is (apparently) where the machine figures out the correct answer on its own.

Supposedly, unsupervised learning can discover something new that has not been found…

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Added by Danko Nikolic on February 14, 2018 at 1:00pm — No Comments

Off the Beaten path – Using Deep Forests to Outperform CNNs and RNNs

Summary:  How about a deep learning technique based on decision trees that outperforms CNNs and RNNs, runs on your ordinary desktop, and trains with relatively small datasets.  This could be a major disruptor for AI.

Suppose I told you that there is an algorithm that regularly beats the performance of CNNs and RNNs at image and text…

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Added by Vincent Granville on February 13, 2018 at 12:00pm — No Comments

Great Sunday Reading

Here is our selection of resources and articles recently featured on DSC: 

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Added by Vincent Granville on February 11, 2018 at 3:14pm — No Comments

Are the Digits of Pi Truly Random? - Must Read for Math and Data Geeks

This article covers far more than the title suggests. It is written in simple English and accessible to quantitative professionals from a variety of backgrounds. Deep mathematical and data science research (including a result about the randomness of Pi, which is just a particular case) are presented here, without using arcane terminology or complicated equations.  

The topic discussed here, under a unified framework, is at the intersection of mathematics, probability theory, chaotic…

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Added by Vincent Granville on February 5, 2018 at 11:00am — No Comments

Great Sunday Reading

Here is our selection of resources and articles featured in the last few days:

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Added by Vincent Granville on February 4, 2018 at 7:28pm — No Comments

What Kind of OLAP Do We Really Need?

The narrow-sensed OLAP

OLAP is part and parcel of a BI application. As the name suggests, the word is an acronym for online analytical processing. Users, frontline employees, to be precise, are responsible for performing various types of data processing online.  

But, the concept of OLAP tends to be used in a very narrow sense. It has almost become an equivalence of multidimensional analysis. Based on a prebuilt data cubic, the analysis performs summarization…

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Added by JIANG Buxing on February 1, 2018 at 4:00am — No Comments

Four Interesting Math Problems

The level in this article is for college students familiar with calculus, This material will be also of interest to college professors looking for new material to teach, or for original exam questions, as well as for business data scientists with some spare time, interested in refreshing their math skills. The problems cover real analysis, mathematical algorithms and numerical precision, correct visualizations, as well as geometry. The third problem is the most interesting one in my…

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Added by Vincent Granville on January 31, 2018 at 10:30am — No Comments

When Variable Reduction Doesn’t Work

Summary:  Exceptions sometimes make the best rules.  Here’s an example of well accepted variable reduction techniques resulting in an inferior model and a case for dramatically expanding the number of variables we start with. 

One of the things that keeps us data scientists on our toes is that the well-established rules-of-thumb don’t always work.  Certainly one of the most well-worn of these rules is the parsimonious model; always seek to create the…

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Added by Vincent Granville on January 31, 2018 at 12:35am — No Comments

Great Sunday Reading

Here is our selection of featured resources and articles published recently on DSC:

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Added by Vincent Granville on January 28, 2018 at 1:59pm — No Comments

What is Clickless Analysis? Can it Simplify Adoption of Augmented Analytics? (Part 1 of 3 articles)

The concept of Clickless Analytics is one that will be happily embraced by business users and by the business enterprise. The reason is simple! Clickless Analytics allows users to find and analyze information without specialized skills, by using natural language.

In this, the first of a three-part series we discuss Clickless Analytics and how it can simplify user adoption of augmented analytics.

What is Clickless Analytics?

Clickless Analytics…

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Added by Kartik Patel on January 25, 2018 at 5:30am — No Comments

Great Sunday Reading

Here is our list of featured articles and resources posted in the last few days::

Featured Resources 

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Added by Vincent Granville on January 21, 2018 at 1:30pm — No Comments

Understanding Supervised, Unsupervised, and Reinforcement Learning

Once we start delving into the concepts behind Artificial Intelligence (AI) and Machine Learning  (ML), we come across copious amounts of jargon related to this field of study. Understanding this jargon and how it can have an impact on the study related to ML goes a long way in comprehending the study that has been conducted by researchers and data scientists to get AI to the state it now is. 

In this article, I will be providing you with a comprehensive definition of supervised,…

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Added by Vincent Granville on January 19, 2018 at 9:01am — No Comments

Data Science is Changing, Data Scientists must Adapt – Here’s Why and How

Summary:  Deep changes are underway in how data science is practiced and successfully deployed to solve business problems and create strategic advantage.  These same changes point to major changes in how data scientists will do their work.  Here’s why and how.

What’s Happening Now

Advanced analytic platforms are undergoing several evolutionary steps at once.  This is the final buildout in the current competitive…

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Added by Vincent Granville on January 16, 2018 at 12:00pm — No Comments

Great Sunday Reading

Here is our selection of new articles and resources featured in the last few days:

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Added by Vincent Granville on January 14, 2018 at 9:35am — No Comments

Easy Dashboards for Everyone Using Google Data Studio

No matter the job, most professionals do some level of analysis on their computer.  There are always some data sets that live outside the walls.  Or, some analyses that we know could be performed better in a not-easily-sharable tool such as excel, R, python, SPSS, SAS and so on.

So how do you share your personal analysis with others?  Often times people export…

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Added by Laura Ellis on January 11, 2018 at 4:30pm — No Comments

Beautiful Number Theory Problem and Sandbox for Data Scientists

The Waring conjecture - actually a problem associated with a number of conjectures, many now being solved - is one of the most fascinating mathematical problems. This article covers new aspects of this problem, with a generalization and new conjectures, some with a tentative solution, and a new framework to tackle the problem. Yet it is written in simple English and accessible to the layman.

I also review a number of famous related mathematical conjectures, including one with a $1…

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Added by Vincent Granville on January 10, 2018 at 6:00pm — No Comments

Great Sunday Reading

Here is our first "Sunday Reading" list of the year, featuring an unusually large number of high quality articles and technical resources posted in the last few days:

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Added by Vincent Granville on January 7, 2018 at 10:00am — No Comments

Digital Twins: Machine Learning & AI

Summary:  Digital Twins is a concept based in IoT but requiring the skills of machine learning and potentially AI.  It’s not completely new but it is integral to Gartner’s vision of the digital enterprise and makes the Hype Cycle for 2017.  It’s a major enabler of event processing as opposed to traditional request processing.…

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Added by Vincent Granville on January 3, 2018 at 10:30pm — No Comments

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