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January 2018 Blog Posts (95)

Jobs, Education, and R

I came across a jaw-dropping article from the Brookings think tank two weeks ago.

The column noted that "household employment data reported by the Bureau of Labor Statistics (BLS)…

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Added by steve miller on January 31, 2018 at 3:00pm — No Comments

R (nmath) ported to javascript (typescript)

Hi, 

I finished my open source project rewriting R (core nmath) in  Javascript (typescript) language,...front end devs and nodejs devs can now use all functions from nmath.

quote from the git repo: https://github.com/jacobbogers/libRmath.js

Javascript ( TypeScript ) Pure Implementation of Statistical R "core" numerical libRmath.so library found …

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Added by Jacob Bogers on January 31, 2018 at 10:00am — No Comments

Sophisticated data strategies call for better analytical features and language diversity

As we move into 2018, Analytical Data Infrastructure (ADI) is becoming a significant topic in business intelligence and analytics. Where Big Data was once an over-hyped, catch-all term, in the coming year we will see organisations move to a place where business-oriented ‘data strategies’ are the major focus. With that shift comes the need for sophisticated, yet easy to use, data science approaches that deliver results back to the business.

It is a point backed up by the 2018 Global…

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Added by Mathias Golombek on January 31, 2018 at 8:00am — No Comments

Hilarious Graphs (and Pirates) Prove That Correlation Is Not Causation

When it comes to storytelling, we have a problem.

It’s not our fault though – as human beings we are hard-wired from birth to look for patterns and explain why they happen. This problem doesn’t go away when we grow up though, it becomes worse the more intelligent we think we are. We convince ourselves that now we are older, wiser, smarter, that our conclusions are closer to the mark than when we were younger (the faster the wind blows the faster the windmill blades…

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Added by Lee Baker on January 31, 2018 at 6:00am — 2 Comments

Aspiring Data Scientists - Get Hired!

Working in Data Science recruitment, we’re no strangers to the mountains you have to climb and pitfalls faced when getting into a Data Science career. Despite the mounting demand for Data Science professionals, it’s still an extremely difficult career path to break into. The most common complaints we see from candidates who have faced rejection are lack of experience, education level requirements, lack of opportunities for Freshers, overly demanding and confusing job role…

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Added by Matt Reaney on January 31, 2018 at 5:00am — 2 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 opinion,…

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Added by Vincent Granville on January 30, 2018 at 9:30pm — 1 Comment

Data Science Graphs (without the code!)

If you read my blog then you'll probably realize there are a few data related topics that I could talk about for days.  This blog dives into a tool called RAW Graphs, which solves for two of them, outlined below. …

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Added by Laura Ellis on January 30, 2018 at 3:30pm — 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…

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Added by William Vorhies on January 30, 2018 at 10:37am — 8 Comments

Selected Recent Articles from Top DSC Contributors - Part 4

This is a new series, featuring great content from our top contributors. Some of these articles are rather technical in nature, but many are business-oriented and written in simple English. The entire series consists of about 120 articles. We intend to publish a new set every two weeks or so. Click here to check out the…

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Added by Vincent Granville on January 30, 2018 at 8:30am — No Comments

Transforming Quantitative Data to Qualitative Data

The two main data types in business are nominal (categorical or qualitative data) and interval data (quantitative or continuous data). Nominal data are just categories on variables such as customer names, and marital status and you cannot do any mathematical operations on this type of data. Bar chart and Pie chart are usually used to describe nominal data. On the other hand, interval data hold numerical values on variables such as income, age, and invoice amount and you can do mathematical…

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Added by Prashanth Southekal, PhD on January 29, 2018 at 9:00pm — 4 Comments

Weekly Digest, January 29

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.

Announcements

  • Enhance your data analysis skills with an online degree from Penn State World Campus. Our programs focus on data and data management. Learn to collect, classify, analyze,…
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Added by Vincent Granville on January 27, 2018 at 8:00pm — No Comments

Python Deep Learning tutorial: Create a GRU (RNN) in TensorFlow

Guest blog post by Kevin Jacobs.

MLPs (Multi-Layer Perceptrons) are great for many classification and regression tasks. However, it is hard for MLPs to do classification and regression on sequences. In this Python deep learning tutorial, a GRU is implemented in TensorFlow. Tensorflow is one of the many Python Deep Learning libraries.

By the way, another…

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Added by Capri Granville on January 27, 2018 at 7:00pm — No Comments

What are the different types of data?

We now live in a data-immersed society. What used to be a term that was mostly the domain of folks in white lab coats is now thrown around by just about everyone--salespeople, soccer players, surfers, you name it. “How much data do you get in your plan?” “Do you get unlimited data?” So the burning question is, what is data?

Data is basically just raw information about something--anything--in some form that…

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Added by Michael Burke on January 26, 2018 at 4:30pm — No Comments

Predict - Prescribe - Prevent: Analytics Value Cycle

Organizations looking for justification to move beyond legacy reporting should review this little ditty from the healthcare industry:

The Institute of Medicine (IOM) estimates that the United States loses $750 billion annually to medical fraud, inefficiencies, and other siphons in the healthcare system…

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Added by Bill Schmarzo on January 26, 2018 at 1:30pm — No Comments

Removing Confusion From Confusion Matrix — Hawaii False Missile Alert

“Missile approaching, Every one run for cover”. People sending final goodbye messages to their loved ones. Family members huddling and praying together. Mother clinging to children, while the father hurriedly makes for a safe getaway for the family to the basement. Imagine the state of…

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Added by Venkat Raman on January 26, 2018 at 11:00am — 3 Comments

Searching on Google Maps using RStudio

Today I've just faced one challenge...

I work on one project, and we need to decide which assets from this company will be visited initially.

As every project, we have limited budget, so we should find some variables to indicate a priority scale.

After some discussion, someone said: let's find the assets close to schools and hospitals. Those must be inspected firstly than others.

Everybody agreed with the voice, but how would be possible to map every school and…

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Added by Thiago Buselato Maurício on January 25, 2018 at 4:00pm — 3 Comments

Unifying the Data Warehouse, Data Lake, and Data Marketplace

There was a time when developing a data warehouse was sufficient to quench the thirst for data, reporting, and analytics of most business users. Not anymore. Organizations have discovered that data can be a valuable business asset. It has taken some time, but finally they realize they can do more with all the data that’s available than just produce simple reports. With the right data they can distinguish themselves from the competition, reduce costs by optimizing business processes, and…

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Added by Amy Flippant on January 25, 2018 at 7:00am — No Comments

2017, the Year of AI

Recently 2017 came to a glittering end and as we look back through the lens of technology, the winner was probably Artificial Intelligence aka AI. It received tremendous success as much as some of the industry leaders commented that 2017 was the ‘Year of AI’. This write-up is an attempt to collate the achievements under the academic and industry.

Academics

Starting off with academics, the sheer volume of papers published is increasing every year. To give you some statistics,…

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Added by Kinnar Kumar Sen on January 25, 2018 at 6:30am — No Comments

A quick start to automatic audio data analysis

In addition to the common use of speech-to-text algorithms, analysis of audio data can provide important knowledge. From sounds made by mechanical devices that pre-cursor an approaching failure to monitoring the dynamics of a crowd of people, audio data can provide important insights.

 

Fortunately, when using existing building blocks, automatic analysis of audio data is not a complicated task. One effective approach is using an audio feature extraction library, followed by…

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Added by Lior Shamir on January 24, 2018 at 5:30pm — No Comments

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