Blaine Bateman
  • Male
  • Superior, CO
  • United States
Share on Facebook

Blaine Bateman's Friends

  • Alex Newman
  • Hebe Li
  • Ken Craig, CIR
  • San Sanych

Gifts Received


Blaine Bateman has not received any gifts yet

Give a Gift


Blaine Bateman's Page

Profile Information

Short Bio:
Blaine Bateman is President of EAF LLC, a consultancy in strategy, market analysis, technology due diligence, and related areas, and has over 30 years international experience. In addition to consulting and research, he writes for a number of tech media outlets. Mr. Bateman graduated in ChE w/Special Honors from the University of Colorado, later receiving a Professional Certificate in Quality Management also from CU, a Certificate in Integrated Strategic Planning from Caltech, a Certificate with Distinction in Game Theory and a Certificate in Cryptography I (both from Stanford MOOCs), completing a Professional Course in Strategy Development at Washington University in St. Louis, a Certificate in Competitive Strategy from LMU Munich MOOC, and a certificate in Finance for non-Finance Professionals (MOOC) from UC Irvine.

Following ten years in government research and management (Deputy Director, National Measurement Laboratory (US DoC NIST) and Chief, Chemical Engineering Division of NIST), Mr. Bateman worked at several start-ups, then 13 years with Laird Technologies, a global specialty electronics firm. Prior to forming EAF, he was VP Strategic Markets, VP Strategic Business Dev., and Global VP of Marketing with Laird. He has experience in Electronics, Automotive, Wireless, Instruments, and Cryogenics. His skills include Strategy, Business Development, Engineering, Product Development, Quality Management, Operations, and RF Technology. Over his career, he has received 18 patents in Chemical Instruments, Antennas, and RF Design.
Job Title:
LinkedIn Profile:

Blaine Bateman's Blog

Exploring Kaggle Titanic data with R Packages naniar and UpSetR

Posted on July 3, 2018 at 10:30am 0 Comments

Recently (6/8/2018), I saw a post about a new R package "naniar", which according to the package documentation, "provides data structures and functions that facilitate the plotting of missing values and examination of imputations. This allows missing data dependencies to be explored with minimal deviation from the common work patterns of 'ggplot2' and tidy data."  naniar is authored…


Simple automated feature selection using lm() in R

Posted on April 30, 2018 at 7:30am 0 Comments

There are many good and sophisticated feature selection algorithms available in R.  Feature selection refers to the machine learning case where we have a set of predictor variables for a given dependent variable, but we don’t know a-priori which predictors are most important and if a model can be improved by eliminating some predictors from a model.  In linear regression, many students are taught to fit a data set to find the best model using so-called “least squares”.  In most…


Extending churn analysis to revenue forecasting using R

Posted on March 27, 2018 at 10:00am 8 Comments

In this article we will review application of clustering to customer order data in three parts.  First, we will define the approach to developing the cluster model including derived predictors and dummy variables; second we will extend beyond a typical “churn” model by using the model in a cumulative fashion to predict customer re-ordering in the future defined by a set of time cutoffs; last we will use the cluster model to forecast actual revenue by estimating the ordering parameter…


Weighted Linear Regression in R

Posted on March 23, 2018 at 6:30am 2 Comments

If you are like me, back in engineering school you learned linear regression as a way to “fit a line to data” and probably called in “least squares”.  You probably extended it to multiple variables affecting a single dependent variable.  In a statistics class you had to calculate a bunch of stuff and estimate confidence intervals for those lines.  And that was probably about it for a long time, unless you were focusing on math or statistics.  You may have…


Comment Wall

You need to be a member of Data Science Central to add comments!

Join Data Science Central

  • No comments yet!

© 2021   TechTarget, Inc.   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service