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November 2016 Blog Posts (95)

Common Coding Situations in Java

 This blog contains some snippets of code that I tend to use in Java.  I acknowledge that somebody else writing this blog might include different code.  Except for a short course at Sun Educational Services, most of my Java programming skills are self-taught.  I’m unsure if people with formal backgrounds in computer science might have different styles and conventions.  Mine have been shaped primarily by my needs.

 

Creating a Graphical User Interface…

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Added by Don Philip Faithful on November 6, 2016 at 8:00am — No Comments

Data Scientist Skill Set

 1         Background

Data science is first and foremost a talent-based discipline and capability. Platforms, tools and IT infrastructure play an important but secondary role. Nevertheless, software and technology companies around the globe spend significant amounts of money talking busin…

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Added by Philipp Diesinger on November 6, 2016 at 8:00am — 1 Comment

Weekly Digest, November 7

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.

Featured Resources and Technical Contributions

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Added by Vincent Granville on November 5, 2016 at 1:30pm — No Comments

An NLP Approach to Analyzing Twitter, Trump, and Profanity

This article was written by Stephanie Kim. Stephanie has a professional experience with data mining and processing including natural language processing along with a small amount of machine learning and script automation.

Who swears more? Do Twitter users who mention Donald Trump swear more than those who mention Hillary Clinton? Let’s find out by…

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Added by Emmanuelle Rieuf on November 4, 2016 at 12:00pm — No Comments

Opinion Mining - Sentiment Analysis and Beyond

Introduction

There’s a lot of buzzword around the term “Sentiment Analysis” and the various ways of doing it. Great! So you report with reasonable accuracies what the sentiment about a particular brand or product is.

Opinion Mining and Sentiment Analysis

After publishing this report, your client comes back to you and…

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Added by Vivek Kalyanarangan on November 4, 2016 at 5:00am — No Comments

How to Approach a Data Intensive Problem

“It is a capital mistake to theorise before one has data.”

― Arthur Conan Doyle, The Adventures of Sherlock Holmes…

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Added by Jari Turkia on November 3, 2016 at 1:30am — No Comments

Thursday News: R, Python, SAS, Data Science, Stats, ML

Here is our new selection of featured articles and resources posted since Monday:

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Added by Vincent Granville on November 2, 2016 at 7:30pm — 5 Comments

IoT Machine Learning – Industrial or Printing Press revolution?

Many people worry that "AI" will usher in a new Industrial revolution where machines replace humans. My take is that it will be more like the Printing press revolution that launched the Age of Enlightenment! The effect will be less of soaring productivity but more of better decision-making leading to a SMARTER society.

 

Part of the problem is the misnomer, "AI or artificial intelligence"…

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Added by PG Madhavan on November 2, 2016 at 12:00pm — No Comments

Detection of Practical Dependency of Variables with Confidence Intervals

This is an article which attempts to detect dependable variables with non-linear method.

I'm going to apply a method for checking variable dependency which was introduced in my previous post. Because the "dependency" I get with this rule is not true dependency as defined in Probability then I will call variables practically dependent at a confidence level…

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Added by Maiia Bakhova on November 2, 2016 at 11:30am — No Comments

How Bayesian Inference Works

Guest blog by Brando Rohrer. Brandon is an author and deep learning developer. He has worked as Principal Data Scientist at Microsoft, as well as for DuPont Pioneer and Sandia National Laboratories. Brandon earned a Ph.D. in Mechanical Engineering from the Massachusetts Institute of Technology.…

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Added by Vincent Granville on November 2, 2016 at 9:30am — 12 Comments

Why is San Francisco on a Data Engineering Hiring Spree?

There are currently over 6,000 job listings on Indeed for “data engineer” in the San Francisco Bay Area. Let’s put this into context:

  • There are 3x more listings for data engineer than there are for data scientist

  • There are 2x more listings for data engineer than…

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Added by Jake Stein on November 2, 2016 at 9:00am — No Comments

21 Great Blogs Posted in the last 12 Months

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. 
.…
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Added by Vincent Granville on November 2, 2016 at 8:00am — No Comments

R, Python or SAS: Which one should you learn first?

Python, R and SAS are the three most popular languages in data science. If you are new to the world of data science and aren’t experienced in either of these languages, it makes sense to be unsure of whether to learn R, SAS or Python.

kd-nuggets-poll-2014-programming-languages

Don’t fret, by the time you’re done reading this article, you will know without a doubt which language is the right one for you.

Overview…

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Added by Aatash Shah on November 1, 2016 at 9:30pm — 8 Comments

Two Hot Growth Areas for IoT

Summary:  If you want to capitalize on all the amazing advancements in data science take a look at these two hot growth areas for IoT.  It's likely that these will be where a lot of venture capital is invested over the next year or two.

A lot of well deserved attention is being directed at speech, image, and text processing.  The tools in this area are the CNNs and RNNs we've reviewed in recent articles.  We'll continue to exploit and refine these capabilities probably…

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Added by William Vorhies on November 1, 2016 at 7:30am — 1 Comment

What Is the Future of Data Warehousing?

There is no denying it – we live in The Age of the Customer. Consumers all over the world are now digitally empowered, and they have the means to decide which businesses will succeed and grow, and which ones will fail. As a result, most savvy businesses now understand that they must be customer-obsessed to succeed. They must have up-to-the-second data and analytical…

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Added by Ronald van Loon on November 1, 2016 at 7:00am — 4 Comments

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