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. 

18 Great Blogs Posted in the last 12 Months…

Guest blog post by Rubens Zimbres, PhD.

This article brings images from my work modeling with Mathematica, my experience as a Business Analyst and also my doctorate lessons. For me, the borders between a properly executed Business Intelligence and Data Science (with substantive knowledge in Management) are fuzzy. 

What is a Data Scientist ? In my understanding, someone…

Here is an update from Zacharias Voulgaris, Data Science Author, Video Producer, and Acquisitions Consultant. The message below is from Zacharias.



1. Produced Videos for O'Reilly Safari on Data Science, Programming Languages, and AI



I have a bunch of videos now live on topics including; becoming a data scientist, artificial Intelligence, and which…

After posting Machine Learning Summarized in One Picture, here is a picture for data science:

I tried to find the source for this picture, but could not. I've found it on LinkedIn, posted by …

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

• Timestamp Data Visualization by…

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, ouliers, regression Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, and many more. To keep receiving these articles, …

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

• Timestamp Data Visualization by Matplotlib +
• Executive Guide to Artificial Intelligence…

When dealing with time series, the first step consists in isolating trends and periodicites. Once this is done, we are left with a normalized time series, and studying the auto-correlation structure is the next step, called model fitting. The purpose is to check whether the underlying data follows some well known stochastic process with a similar auto-correlation structure, such as ARMA processes, using tools such as…

More and more people are talking about the new economy, and in particular, the role played by robots. As jobs are being eliminated and replaced by robots, governments are losing tax money. There are discussions as to whether robots should be taxed. …

Actually, this is about two R versions (standard and improved), a Python version, and a Perl version of a new machine learning technique recently published here. We asked for help to translate the original Perl script to Python and R, and finally decided to work with …

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.

Upcoming DSC Webinar

• A Dashboard Worth 1000 Words: Communicating Insights…

Recently we read a lot about fake news, alternate facts and journalism lies. Companies like Facebook develop data science algorithms to detect these postings, based among other things on crowd sourcing (collective intelligence.)

But can the data scientist, with her inquisitive mind and strong sense of numbers and probabilities, use her brain to assess how true a piece…

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

• The Mathematics of Machine Learning 
• Designing the Data Management Infrastructure of Tomorrow …

Guest blog post by Wale Akinfaderin, PhD Candidate in Physics. 

In the last few months, I have had several people contact me about their enthusiasm for venturing into the world of data science and using Machine Learning (ML) techniques to probe statistical regularities and build impeccable data-driven products. However, I've observed that some actually lack the necessary mathematical intuition and…

This contribution is from David Corliss. David teaches a class on this subject, giving a (very brief) description of 23 regression methods in just an hour, with an example and the package and procedures used for each case. 

Here you can check the webcast done for Central Michigan University. The slide deck can be found…

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 2017, April 3 - 5 2017, JW Marriott Union Square, San Francisco, CA  -- Empower yourself to become more valuable in your…

Guest blog by Kevin Gray.. Kevin is president of Cannon Gray, a marketing science and analytics consultancy. 

Regression is arguably the workhorse of statistics. Despite its popularity, however, it may also be the most misunderstood. Why? The answer might surprise you: There is no such thing as Regression. Rather, there are a large number of statistical methods that are called…

t-Distributed Stochastic Neighbor Embedding (t-SNE) is a (prize-winning) technique for dimensionality reduction that is particularly well suited for the visualization of high-dimensional datasets. The technique can be implemented via Barnes-Hut approximations, allowing it to be applied on large real-world datasets.…

The technique presented here blends non-standard, robust versions of decision trees and regression. It has been successfully used in black-box ML implementations.

In this article, we discuss a general machine learning technique to make predictions or score transactional data, applicable to very big, streaming data. This hybrid technique combines different algorithms to boost accuracy, outperforming each algorithm taken separately, yet it is simple enough to be reliably…

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

• How to Clean Your Data Quickly in 5 Steps 
• 10 Articles and Tutorials about Outliers …