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February 2016 Blog Posts (93)

Groundhogs. I choose to celebrate National Prediction Day

Guest blog by Jay Gendron, Associate Data Scientist at Booz Allen Hamilton; Author; Data Analytics; Speaker.

Happy Groundhog Day! Happy National Prediction Day?

In today’s edition of “Coffeehouse Connect” we take a look at a major predictive event in the United States that occurs each year on February 2.

Today is Groundhog Day. It occurs in…

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Added by Vincent Granville on February 3, 2016 at 8:57pm — No Comments

Weekly Digest, February 8

Starred articles are new additions or updated content, posted between Thursday and Sunday. The weekly digest has six sections: (1) Featured Resources and Technical Contributions, (2) Featured Articles and Case Studies, (3) From our Sponsors, (4) News, Events, Books, Training, Forum Questions, (5) Picture of the Week, and (6) Syndicated Content.

The full version is always published Monday.…

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Added by Vincent Granville on February 3, 2016 at 4:30pm — No Comments

Are You Stuck in Analytics 2.0?



Summary:
 It’s time to start thinking about whether our analytic tools and techniques are up to what it takes to move on to Analytics 3.0.

 

In 2013 Thomas Davenport proposed that analytic leaders are leaving…

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Added by William Vorhies on February 3, 2016 at 3:33pm — 4 Comments

Open Data in Government

Open data has several definitions but our preferred one at Data To Value is from the Open Data Institute‘Open data is data that anyone can access, use and share.’ Simple really but there is a follow-on – ‘For data to be considered ‘open’, it must be published in an accessible…

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Added by Zygimantas Jacikevicius on February 3, 2016 at 6:30am — No Comments

Big Data Insights - IT Support Log Analysis

This post brings forth to the audience, few glimpses (strictly) of insights that…

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Added by Pradeep Mavuluri on February 3, 2016 at 2:45am — No Comments

7 Ways to Perplex a Data Scientist

On the heels of a report showing the inefficacy of government-run cyber security, it’s imperative to understand the limitations of your system and model. As that article shows, in addition to bureaucratic risk the government also needs to worry about gaming-the-bureaucracy risk! Government snafus aside, data science has…

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Added by Brian Rowe on February 2, 2016 at 7:00am — No Comments

Introduction to data quality

How many times have you heard managers and colleagues complain about the quality of the data in a particular report, system or database? People often describe poor quality data as unreliable or not trustworthy. Defining exactly what high or low quality data is, why it is a certain quality level and how to manage and improve it is often a trickier…

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Added by Zygimantas Jacikevicius on February 2, 2016 at 2:00am — No Comments

How Airlines Measure Loyalty

An ongoing debate in the loyalty world is what type of customer is more important? One that spends big on airline tickets or one that filters millions of credit card miles through the banks?

Recently at the Loyalty Event in San Diego, Mike Hecht from Delta noted that they don't mind whether their customers are loyal due to credit card spend, or…

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Added by Mark Ross-Smith on February 2, 2016 at 2:00am — No Comments

Stop Hiring Data Scientists Until You're Ready for Data Science

Blog post by Great Roberts. This is a great article to print and/or forward to HR and specifically the data scientist hiring manager in your organization.

I had yet another call today with a brilliant data scientist working inside of a Human Resources Department of a major business. This HR data scientist has both a strong analytics and predictive analytics background. She has a Bachelor’s Degree in Statistics and a Master’s Degree in Predictive Analytics. She excels in R,…

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Added by Mike Kennedy on February 2, 2016 at 2:00am — No Comments

Sentiment Analysis with the bag-of-words

As a precursor to research about Sentiment Analysis with Text Classifiers (Naive Bayes, Maximum Entropy, SVM), Sentiment Analysis with bag-of-words was done and Positive / Negative Sentiment was detected with an accuracy of 60%. This is when only unigrams are used. This percentage will be much when bigrams or trigrams are used (in a next blog-post). See the results at:

part 1: http://tinyurl.com/gnlfqqm

part 2:…

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Added by Ahmet Taspinar on February 1, 2016 at 1:30pm — 1 Comment

A tale about LDA2vec: when LDA meets word2vec

catdog_word2vec_cropped

A few days ago I found out that there had appeared lda2vec (by Chris Moody) – a hybrid algorithm combining best ideas from well-known LDA (Latent Dirichlet Allocation) topic modeling algorithm and from a bit less well-known tool for language modeling named word2vec.

And now I’m going to tell you a tale about lda2vec and my attempts to try it and compare with simple LDA…

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Added by Nikitinsky Nikita on February 1, 2016 at 12:00pm — 1 Comment

Correlation Coefficient in Legal Data

 

This is a lesson  from one of our Data Science for Lawyers Workshops (Moderately Advanced). It is part of our Quantative Analysis in…

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Added by Mkhuseli Mthukwane on February 1, 2016 at 11:04am — No Comments

Polygot Persistence with OrientDB

The advent of NoSQL databases has lead many application developers, designers, and architects to apply the most appropriate means of data storage to each specific aspect of their systems, and this may involve implementing multiple types of database and integrating them into a single solution. The result is a polyglot solution.

Designing and implementing a polyglot system is not a straightforward task and there are a number of questions that need to be addressed…

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Added by Raghavan Madabusi on February 1, 2016 at 7:41am — No Comments

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