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Featured Blog Posts – January 2017 Archive (85)

The Periodic Table Of AI

This article was written by Kris Hammond.

This is an invitation to collaborate. In particular, it is an invitation to collaborate in framing how we look at and develop machine intelligence. Even more specifically, it is an invitation to collaborate in the construction of a Periodic Table of AI.

Let’s be honest. Thinking about Artificial Intelligence has proven to be difficult for us.  We argue constantly about what is and is not AI.  We…

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Added by Emmanuelle Rieuf on January 17, 2017 at 1:30pm — 1 Comment

5 Types of Recommenders

Summary:  There are five basic styles of recommenders differentiated mostly by their core algorithms.  You need to understand what’s going on inside the box in order to know if you’re truly optimizing this critical tool.

 

In our first article, “…

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Added by William Vorhies on January 17, 2017 at 9:00am — 2 Comments

10 Common NLP Terms Explained for the Text Analysis Novice

If you’re relatively new to the NLP and Text Analysis world, you’ll more than likely have come across some pretty technical terms and acronyms, that are challenging to get your head around, especially, if you’re relying on scientific definitions for a plain and simple explanation.

We decided to put together a list of 10 common terms in Natural Language Processing which we’ve broken down in layman terms, making them easier to understand. So if you don’t know your “Bag of Words”…

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Added by Mike Waldron on January 17, 2017 at 1:30am — 1 Comment

New Comprehensive Taxonomies on Mobile Security and Malware Analysis

Our article "New Comprehensive Taxonomies on Mobile Security and Malware Analysis" has been published in International Journal of Information Security Science (IJISS). The poster below summarizes the article.

The three academic taxonomies (IEEE Taxonomy,…

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Added by Gürol Canbek on January 16, 2017 at 11:30pm — No Comments

Logistic Regression using python

This article was posted by Arpan Gupta (Indian Institute of Technology).

Let’s learn from a precise demo on Fitting Logistic Regression on Titanic Data Set for Machine Learning

Description:On April 15, 1912, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew.…

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Added by Emmanuelle Rieuf on January 16, 2017 at 11:00am — No Comments

Learn Support Vector Machine (SVM) from Scratch in R

This tutorial describes theory and practical application of Support Vector Machines (SVM) with R code. It's a popular supervised learning algorithm (i.e. classify or predict target variable). It works both for classification and regression problems. It's one of the sought-after machine learning algorithm that is widely used in data science competitions.

What is Support Vector Machine?



The main idea of support vector machine is to…

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Added by Deepanshu Bhalla on January 16, 2017 at 7:30am — No Comments

HealthCare Industry’s Savior: Using the Benford's Law (The Law of First Digit) to Debunk the Fraudsters

As the world is getting more tech savvy and advancements made in the information technology especially in the healthcare industry has opened areas in data mining and machine learning. Within the area of data mining one technique which has gained a lot of popularity as well as skepticism among the auditors and fraud detectives is Benford’s Law or “The Law of First digit.

In the past some researchers in Canada used the Benford’s Law distribution to detect anomalies within the claims…

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Added by Sunil Kappal on January 16, 2017 at 5:12am — 5 Comments

Just get rid of your billion dollar Data

Data isn't your business.It's just by-product of doing business.I know you want to get rid of those redundant data which suck up a lot of storage space.From years companies are known to pay extra to eradicate waste leftover from the production process.Times have changed, though. Through genius innovation, many entrepreneurs have taken what was once useless sludge and transmuted it into massive profits.

After yielding their finished product, breweries in the late 19th…

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Added by vivek upadhyay on January 15, 2017 at 9:30am — No Comments

This is how Analytics is changing the game of Sports!!

Analytics and Big Datahave disrupted many industries, and now they are on the edge of scoring major points in sports. Over the past few years, the world of sports has experienced an explosion in the use of analytics
Till few years back experience, gut feelings, and superstition have traditionally shaped the decision making process in…
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Added by Sandeep Raut on January 15, 2017 at 7:00am — 1 Comment

Weekly Digest, January 16

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

  • Marketing Analytics and Data Science 2017April 3 - 5 2017, JW Marriott Union Square, San Francisco, CA.  -- Empower yourself to become more valuable in your…
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Added by Vincent Granville on January 14, 2017 at 9:00am — No Comments

Crosswave Differential Event Model

I have been writing about the Crosswave Differential Algorithm for a number of years. I described in previous blogs how the algorithm emerged almost by accident while I was attempting to write an application intended to support quality control. In this blog I will be discussing the event model that powers the algorithm. Events are the details and circumstances…

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Added by Don Philip Faithful on January 14, 2017 at 5:27am — No Comments

We run faster than you: Factors affecting marathon results

Contributed by David Richard Steinmetz. He enrolled 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 their third project - Web Scraping, due on 6th week of the program. The original article can be found here.

We run faster than you: an analysis of marathon results…

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Added by NYC Data Science Academy on January 13, 2017 at 2:30pm — No Comments

Who came up with the name Big Data?

Big Data has truly come of age in 2013 when Oxford English Dictionary introduced the term “Big Data” for the first time in its dictionary. That of course begs the question ‘When was the term Big Data first used and Why?’. My curiosity led me to lot of research material but I relied mostly on Mr. Gil Press’s “A Very Short History of Big data” from Forbes, Mr. Steve Lohr’s “The Origins of ‘Big Data': An Etymological Detective Story“ from The New York Times, Mr. Mark van Rijmenam’s “A Short…

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Added by Ramesh Dontha on January 13, 2017 at 8:00am — No Comments

5 Ways to Use Analytics to Improve Customer Responsiveness

Big data and analytics are proving to be a great way to bring about positive results regarding operations. Even though the success of a business still relies on keeping the customer happy, it's no secret that social media and new technology have a hand in it. This is why analytics is such a great option when improving upon relationships with the customer.

1. Utilize Social and Mobile Roles

When a company wants to find out what their…

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Added by Sasha Brown on January 13, 2017 at 5:23am — No Comments

Improving Prediction of Office Room Occupancy Through Random Sampling

Introduction:

In many cases, you may think that you have a Big Data problem, when in reality you just have a lot of data that a simple sampling can result in great accuracy.  In todays blog, I decided to use office room occupancy dataset provided by"Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models. Luis M.…
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Added by Dalila on January 12, 2017 at 9:00am — 1 Comment

Notable Fundraising Highlights of Machine Learning Startups in 2016

2016 has been a prolific year for Machine Learning/AI companies in all fronts. In this post I have tried to capture some notable funding rounds and acquisitions of Machine Learning (ML) startups that took place last year. Admittedly there are too many of these events and I have probably missed some, but I am reasonably certain that I have covered a good chunk of them. Before jumping to the table below, I would like to cover some general themes first:

1.             Companies involved…

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Added by Al Gharakhanian on January 11, 2017 at 7:40pm — No Comments

46 SQL Job Interview Questions for Data Scientists

This article was posted by Ankit Gupta.  

Introduction: 

If there is one language, every data science professional should know – it is SQL. SQL stands for Structured Query Language. It is a programming language used to access data from relational databases.

We conducted a skilltest to test our community on SQL and it gave 2017 a kicking start. A total of 1666 participants registered for the skilltest.

This test…

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Added by Emmanuelle Rieuf on January 11, 2017 at 11:30am — 6 Comments

Top 10 AI events of 2016

This could a little late given that we have already embarked upon a new year. But it could be worthwhile looking back for a moment...

2016 was definitely the year of AI in the recent technology timeline. If that’s a little far fetched, considering the wide use of drones, advances in VR/AR and blockchain, that’s because of the ‘bias’ (read enthusiasm) in my neurons. I haven’t been for long in this field but after Deepmind’s paper a few years back, this year was…

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Added by Anurag Priyadarshi on January 11, 2017 at 4:00am — No Comments

How To Create A 360-Degree Customer View Using Data

How valuable would it be to know everything about your customer’s interactions with your competition? Creating a 360-degree customer view is considered the holy grail of customer intelligence, and you can create it, today.

Would you like to know how much they’re spending, when they’re spending, why they’re buying with the competition and not you, what…

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Added by Mark Ross-Smith on January 11, 2017 at 3:31am — No Comments

Understanding and Selecting Recommenders

Summary:  In this multi-part series we walk through the full landscape of Recommenders.  In this article we cover business considerations as well as issues for Recommenders as a group.  In the next articles we’ll discuss the details of the five major types of recommenders, improving their performance, and finally the coming impact of deep learning on Recommenders.

 …

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Added by William Vorhies on January 10, 2017 at 9:00am — 4 Comments

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