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Featured Blog Posts (3,055)

Weekly Digest, March 27

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


Added by Vincent Granville on March 25, 2017 at 7:58am — No Comments

7 Data Videos Built with R

These videos display data sets with a time dimension: each frame in the video shows the data set at a given time, thus showing how the data evolved over time. To learn about how these videos were produced, click here and also here and…


Added by Vincent Granville on March 25, 2017 at 7:30am — 1 Comment

Scraping NSF Awards to Create Database of Active STEM Researchers

Contributed by Nathan Stevens. He enrolled in the NYC Data Science Academy 12-week full time Data Science Bootcamp program taking place between September 23, 2016 and December 23, 2016. The original article can be found here.


There a numerous use cases for having a searchable database of active STEM (Science Technology…


Added by NYC Data Science Academy on March 17, 2017 at 11:30am — No Comments

Reaping Big from Big Data Analytics

This guest blog is contributed by Evans Walsh

For the remaining part of 2017, companies will have to come to terms with the new reality in town; it is not all about what you know. Instead, it is what you do with it. Various gurus have already said that 2017 is the year when Google Analytics and big data will go main stream. It is the year when analytics will not only reflect performances but also drive major businesses.

For companies that might be falling…


Added by Shay Pal on March 24, 2017 at 6:30pm — No Comments

Little Bee books: Tough topics simply explained

This is a nice collection of free eBooks to learn the ropes on topics covering Hadoop, machine learning, Spark, analytics, and more.

The Little Bee series of books provides an overview of the hot topics in data and analytics, giving you a snapshot of each technology and its potential benefit to your organisation. These books will not make you an expert, but they will improve your understanding and open the door to new ideas.

The subject of data and…


Added by Emmanuelle Rieuf on March 20, 2017 at 4:00pm — No Comments

Machine Learning: An In-Depth Guide - Overview, Goals, Learning Types, and Algorithms

This article was written by Alex Castrounis. Alex is the founder of InnoArchiTech


Machine learning is a very hot topic for many key reasons, and because it provides the ability to automatically obtain deep insights, recognize unknown patterns, and create high performing predictive models from data, all without requiring explicit programming…


Added by Emmanuelle Rieuf on March 22, 2017 at 3:00pm — No Comments

Getting Started with Deep Learning

This article was written by Matthew Rubashkin. With a background in optical physics and biomedical research, Matthew has a broad range of experiences in software development, database engineering, and data analytics.

At SVDS, our R&D team has been investigating different deep learning technologies, from recognizing images of trains to speech recognition. We needed to build a pipeline for ingesting…


Added by Emmanuelle Rieuf on March 24, 2017 at 12:30pm — No Comments

R for hackers

Last Sunday at Trivadis Tech Event, I talked about R for Hackers. It was the first session slot on Sunday morning, it was a crazy, nerdy topic, and yet there were, like, 30 people attending! An emphatic thank you to everyone who came!

R a crazy, nerdy topic, - why that, you'll be asking? What's so nerdy about using R?

Well, it was about R. But it was neither an introduction ("how to get things done quickly with R"), nor was it even about data science. True, you…


Added by Sigrid Keydana on March 24, 2017 at 2:30am — No Comments

5 Kinds of Exploratory Questions You May Be Asking Yourself

An exploratory study must always be designed and executed in order to answer a number of a-priory questions. Our experience in dozens of scientific…


Added by Ray G. Butler on March 23, 2017 at 4:30am — No Comments

17 Most Commented Data Science Blogs

This selection is not about the most read articles, but instead about the most commented ones. All of them have a significant number of comments. And many times, these comments are even more interesting and resourceful than the original article. So this time, I invite you to read the comments attached to these articles. They can be found below each article.


Added by Vincent Granville on March 21, 2017 at 7:30am — No Comments

Free Machine Learning eBooks - March 2017

Here are three eBooks available for free.


Edited by Abdelhamid Mellouk and Abdennacer Chebira

Machine Learning can be defined in various ways related to a scientific domain concerned with the design and development of theoretical and implementation tools that allow building systems with some Human Like intelligent behaviour.

Machine Learning addresses more specifically the ability to…


Added by Emmanuelle Rieuf on March 20, 2017 at 4:00pm — 5 Comments

Connecting the dots: the art and science of managing your workday

Recently, an HR expert told me that to progress in my career I’d need to spend at least 50% of my time managing laterally. Laterally as in not “up” to my boss or “down” to the team I lead.

My immediate instinct was to discard this flat out: after all, how would someone even measure this? Designing an experiment so large as to statistically prove the 50% is extremely tough. There are hundreds of factors contributing to every…


Added by Catalin Ciobanu on March 23, 2017 at 5:30am — No Comments

Walk-through Of Patient No-show Supervised Machine Learning Classification With XGBoost In R


This is a project I've been working on for some time to help improve the missed opportunity rate (no-show rate) at all medical centers. It demonstrates how to extract datasets from an SQL server and load them directly into an R environment. It also demonstrates the entire machine learning process, from engineering new features, tuning and training the model, and finally measuring the model's performance. I would like to share my results and methodology as a guide to help…


Added by James Marquez, MBA, PMP on March 21, 2017 at 8:30am — No Comments

Best countries to work for software engineers, developers and data scientists in 2017

From my experience, English speakers can find the most jobs in the U.S. (West Coast, obviously), United Kingdom (London), Ireland, Netherlands (Amsterdam), Switzerland, and Belgium. New Zealand and Australia are pretty popular among developers who love the laid-back lifestyle.

But the scenarios change when we talk about non-English speaking nations. Japan is growing exponentially; Russia and China have a huge culture of programming, and IT companies are growing rapidly in these…


Added by ARPIT MISHRA on March 22, 2017 at 1:00am — No Comments

Flafka: Big Data Solution for Data Silos

From the previous post on “Poor Data Management Practices“,  the discussion ended with a high level approach to one possible solution for data silos. Traditional approaches for solving the data silo problem can cost millions of dollars (even for a moderately sized company), and typically…


Added by Randall V Shane on March 22, 2017 at 1:30pm — No Comments

Goodbye Age of Hadoop – Hello Cambrian Explosion of Deep Learning

Summary:  Some observations about new major trends and directions in data science drawn from the Strata+Hadoop conference in San Jose last week.


I’m fresh off my annual field trip to the Strata+Hadoop conference in San Jose last week.  This is always exciting, enervating, and…


Added by William Vorhies on March 20, 2017 at 4:48pm — No Comments

20 Great Blogs Posted in the last 12 Months - New Edition

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. 

20 Great Blogs Posted in the last 12…


Added by Vincent Granville on March 21, 2017 at 3:48pm — No Comments

Difference of Data Science, Machine Learning and Data Mining

Data is almost everywhere. The amount of digital data that currently exists is now growing at a rapid pace. The number is doubling every two years and it is completely transforming our basic mode of existence. According to a paper from IBM, about 2.5 billion gigabytes of data had been generated on a daily basis…


Added by Leonard Heiler on March 20, 2017 at 10:30am — 1 Comment

How Airline Loyalty Programs Use Big Data To Drive Record Revenues

It’s often thought that loyalty programs are designed to reward customers with special offers, treats, and discounts in the hope of retaining their business and…


Added by Mark Ross-Smith on March 20, 2017 at 11:30am — No Comments

The Four Stages of a Chatbot’s Business Intelligence Evolution

The Four Stages of a Chatbot’s Business Intelligence Evolution

I see four stages in the progression of chatbot-like AIs interacting with business systems for the purpose of providing actionable business intelligence.

Stage 1) Single Numeric Response

Question :…


Added by Eduardo Siman on March 20, 2017 at 7:00am — No Comments

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