Machine Learning Times
EXCLUSIVE HIGHLIGHTS
AGI Is Infeasible. Instead, Pursue Superhuman Adaptable Intelligence
  Originally published in Forbes On a recent episode of the...
Artifact-Driven Development: Making It Possible to Query Large Analytics and AI Projects
 A practical introduction to making complex project structure explicit...
Incoherent AGI Hype Spurs An Industrywide Pivot To Hybrid AI
  Originally published in Forbes Recently on The Dr. Data Show,...
The AI Paradox: More Humanlike Means Less Autonomous
  Originally published in Forbes The AI executives are at...

Elder Research

3 Ways to Test the Accuracy of Your Predictive Models

 Editor’s note: This article compares measures for model performance. Note that “accuracy” is a specific such measure, but that this article uses the word “accuracy” to generically refer to measures in general. In data mining, data scientists use algorithms to identify previously unrecognized patterns and trends hidden within vast amounts of structured and unstructured information.

It is a Mistake to…. Ask the Wrong Question

 (Part 4 (of 11) of the Top 10 Data Mining Mistakes, drawn from the Handbook of Statistical Analysis and Data Mining Applications) It is very important to have the right project goal; that is, to aim at...

It is a Mistake to…. Rely on One Technique

 (Part 3 of 11 of the Top 10 Data Mining Mistakes, drawn from the Handbook of Statistical Analysis and Data Mining Applications) -John Elder (elder datamininglab com) “To a little boy with a hammer, all...

The Musings of a (Young) Data Scientist

I quit my job as a Mathematical Statistician after one year and two days. I left behind great benefits, job security, and guaranteed raises entirely because I felt unfulfilled. I was bored, lacked a sense of a...

Big Data Continued…

Big Data is not a singular concept but rather a label for a range of data issues. A few months ago I wrote an article about the Volume, Velocity, and Variety (and other “V’s”) of big...

It is a Mistake to… Focus on Training Results

(Part 2 of 11 of the Top 10 Data Mining Mistakes, drawn largely from Chapter 20 of the Handbook of Statistical Analysis and Data Mining Applications)...

Yet Another Big Data Article

It's like an irritating fly buzzing around your head – "Big Data". Do I have to hear the term one more time? As a Data Scientist who interacts with hard data problems on a daily basis, the...

Top 10 Analytic Mistakes–Today #0: Lacking Relevant Data

Mining data to extract useful and enduring patterns remains a skill arguably more art than science. Pressure enhances the appeal of early apparent results, but it is all too easy to fool oneself. How can one resist...

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