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All Blog Posts Tagged 'predictive modeling' (141)

12 Great Data Science Articles by Bill Vorhies

Bill Vorhies is Editorial Director for DataScienceCentral, and President and Chief Data Scientist at Data-Magnum, providing predictive analytics and big data infrastructure projects as a service. Bill has been an active commercial predictive modeler since 2001.

Below, you will find a selection of his articles posted in the last two years. To check out his most recent…


Added by Vincent Granville on June 2, 2016 at 9:00am — No Comments

Debunking the 68 Most Common Myths About Big Data – Part 2

Summary:  Continuing from out last article, we searched the web to find all of the most common myths and misconceptions about Big Data.  There were a lot more than we thought.  Here’s what we found. Part 2.


If you caught…


Added by William Vorhies on May 10, 2016 at 2:00pm — 1 Comment

The New Rules for Becoming a Data Scientist

Summary:  What do you need to do to get an entry level job in data science?

This article is written for anyone who is considering becoming a data scientist.  That includes young people just starting their bachelor’s degrees and folks in the first two or three years of their careers who want to make the switch.

It’s not for folks who…


Added by William Vorhies on April 26, 2016 at 2:30pm — 10 Comments

20 Data Science and Mathematical Challenges

I invite you to solve these challenges yourself before reading the solutions (for some of these problems) or hints to help you tackle these problems.

  1. Interesting Recursive Formula
  2. Identifying patterns in…

Added by Vincent Granville on April 19, 2016 at 9:44am — No Comments

15 Most Controversial Data Science Articles

These articles were controversial in the sense that they highlighted the differences between data science and other disciplines, at a time when many believed that data science was just old stuff being re-branded, or being practiced by people knowing nothing about statistics. Ironically, some of the old stuff actually re-branded itself as data science, not the other way around.…


Added by Vincent Granville on March 24, 2016 at 6:30pm — No Comments

When Data Viz Trumps Statistics

Summary:  Which is the most critical element in data exploration, statistics or data visualization?  The answer is a little like the lyric ‘love and marriage, you can’t have one without the other’.  It can be tempting to skip the data visualization but it’s frequently the key to making sure we aren’t heading down the completely wrong path.



Added by William Vorhies on March 23, 2016 at 8:35am — No Comments

Can A Cow be an IoT Platform?

Summary:  This is my favorite IoT story. We are so used to IoT platforms being physical objects that we forget about the potential for biologics.  In terms of direct economic reward little will compare to this story about the IoT and cows.

This is my favorite IoT story which I first heard from Joseph Sirosh, CVP of Machine Learning for Microsoft at the spring Strata convention in San Jose.  We are so used to IoT platforms being physical objects like cars…


Added by William Vorhies on March 21, 2016 at 7:43am — 4 Comments

7 Cases Where Big Data Isn’t Better

Summary:  It’s become almost part of our culture to believe that more data, particularly Big Data quantities of data will result in better models and therefore better business value.  The problem is it’s just not always true.  Here are 7 cases that make the point.


Following the literature and the technology you would think there is…


Added by William Vorhies on March 10, 2016 at 2:15pm — 5 Comments

MIT Algorithm Predicts Rogue Waves in Real Time to Save Lives

Using AI and data science, an MIT team was able to accurately predict rogue waves coming out of the blue in the middle of the ocean, in near real time, to help sailors change their navigation path and avoid destruction and death. Rogue waves, while rare, are unpredictable, tall (up to 100 feet) and devastating. The physical mechanism producing these waves is well understood, and is typically modeled using rotating elements.…


Added by Vincent Granville on March 3, 2016 at 6:00pm — 3 Comments

Exponential Smoothing of Time Series Data in R

Guest blog post by Jeffrey Strickland. Originally posted here.
This article is not about smoothing ore into gems though your may find a…

Added by Vincent Granville on February 24, 2016 at 9:41pm — 1 Comment

5 Ways to Get Fired as a Data Scientist

Guest blog by Justin B. Dickerson, PhD, MBA, PStat, Chief Data Scientist at Snap Advances. 

Okay, that headline was meant to get your attention. But lately, I've been thinking about this crazy circus we call data science and how everyone seems to think data scientists are invaluable, treasured, and potentially "un-fireable" in this age of data scientist negative…


Added by Vincent Granville on February 3, 2016 at 9:19pm — 7 Comments

Introduction to Outlier Detection Methods

This post is a summary of 3 different posts about outlier detection methods. 

One of the challenges in data analysis in general and predictive modeling in particular is dealing with outliers. There are many modeling techniques which are resistant to outliers or reduce the impact of them, but still detecting outliers and understanding them can lead to interesting findings. We generally define outliers as samples that are exceptionally far from the mainstream of data.There is no rigid…


Added by Shahram Abyari on January 18, 2016 at 3:30pm — 5 Comments

Weekly Digest, January 11

Starred articles are new additions or updated content, posted between Thursday and Sunday. The weekly digest has 6 sections: (1) Featured Articles and Case Studies, (2) Featured Resources and Technical Contributions, (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.…


Added by Vincent Granville on January 6, 2016 at 8:00pm — No Comments

24 Uses of Statistical Modeling (Part I)

Here we discuss general applications of statistical models, whether they arise from data science, operations research, engineering, machine learning or statistics. We do not discuss specific algorithms such as decision trees, logistic regression, Bayesian modeling, Markov models, data reduction or feature selection. Instead, I discuss frameworks - each one using its own types of techniques and algorithms - to solve real life problems.   

Most of the entries below are found in…


Added by Vincent Granville on December 14, 2015 at 10:00am — No Comments

A data scientist shares his passions

\We asked our staff data scientist what motivates him, and here's what he said:

My passions:

  1. Data Science research but not in an academic or corporate environment.
  2. Developing new, synthetic metrics (to measure yield or for data reduction), and robust, simple, scalable techniques to handle big, unstructured, messy, flowing data -- avoiding the curse of big data.
  3. Offering awards to winners in our competitions.
  4. Delivering…

Added by L.V. on December 13, 2015 at 2:30pm — 5 Comments

49 Machine Learning Resources and Related Articles from Top Bloggers

Starred articles are candidates for the picture of the week. A comprehensive list of all past resources is found here. We are in the process of automatically categorizing them using indexation and automated tagging…


Added by Vincent Granville on December 6, 2015 at 8:46pm — No Comments

The ABCD's of Business Optimization

I was trying to find some good domain name for our upcoming business science website, when something suddenly became clear to me. Many of us have been confused for a long time about what data science means, how it is different from statistics, machine learning, data mining, or operations research, and the rise of the data scientist light - a new species of coders who call themselves data scientist after a few hours of Python/R…


Added by Vincent Granville on November 26, 2015 at 11:00am — 2 Comments

How Publishers Utilize Big Data for Audience Segmentation

By Chuck Currin and Arvid Tchivzhel, Mather Economics

Audience segmentation of their readers is a relatively new undertaking for publishers. The publishing business model, historically, has relied heavily on advertising revenue, and the principal audience information that a publisher possessed was focused on characteristics valuable to their advertisers. As subscription revenue has become half or more of total revenue, the return on audience analytics and segmentation has…


Added by Arvid Tchivzhel on November 17, 2015 at 5:28am — No Comments

Eight IOT Analytics Products

Vitria IoT…


Added by Gilboz on November 17, 2015 at 12:20am — 1 Comment

600 websites about R

Anyone interested in categorizing them? It could be an interesting data science project, scraping these websites, extracting keywords, and categorizing them with a simple indexation or tagging algorithm. For instance, some of these blogs cater about stats, or Bayesian stats, or R libraries, or R training, or visualization, or anything else. This indexation technique…


Added by L.V. on November 7, 2015 at 2:30pm — 2 Comments

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