Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Re-examining Model Evaluation: The CRISP Approach
 The performance of prediction models can be judged using...
An Agile Approach to Data Science Product Development
 Introduction With the huge growth in machine learning over...
Wise Practitioner – Predictive Analytics Interview Series: Haig Nalbantian at Mercer – BIZ
 By: Eric Siegel, Founder, Predictive Analytics World for Business...
Is What You Did Ethical? Helping Students in Computational Disciplines to Think About Ethics
 In addition to this article, Dr. Priestly will also...

Big Data

The Great Analytical Divide: Data Scientist vs. Value Architect

 In the analytics space, it is quite common for many organizations to have a team of data miners who are now referred to as data scientists and a team of business users who are often referred to as value architects. It has been a common practice ever since the first direct marketing models were produced

What does Business Intelligence integration with R really mean

  Do the BI vendors’ claims really stack up? “A little prediction goes a long way” wrote Eric Siegel in his popular Predictive Analytics book. True, predictive analytics is now part and parcel of most Business Intelligence...

How bad data can lead to good decisions (sometimes)

 Before companies can profit from big data, they often must deal with bad data. There may indeed be gold in the mountains of information that firms collect today, but there also are stores of contaminated or “noisy”...

CPG companies could improve business performance with better use of analytics, Accenture study finds

 The majority of consumer packaged goods (CPG) companies are failing to place analytics at the heart of their decision-making process, limiting their ability to improve the customer  experience and gain business advantage, a study by Accenture has...

Thriving in a Big Data World

 Three recent books offer managers expert perspectives on the increasing power and importance of analytics. U.S. President Barack Obama’s 2012 campaign owed much of its success to quantitative analysis, with staffers able to identify, for example, which...

Big predictions for Big Data for community banks

 Department store conglomerate Target Brands Inc. knows when its female customers are pregnant long before they start buying cribs. Google Inc. was able to track the H1N1 flu in real-time using Internet search queries when the government...

5 Ways to Become Extinct as Big Data Evolves

 The need to adopt sophisticated data analytics has become widely apparent to businesses recently, and the necessity of adopting “Big Data” analytics approaches is only becoming more evident. Gartner’s report on Big Data Adoption in 2013 found...

2014 Big Data Predictions from IDC and IIA

 Both IDC and The International Institute of Analytics (IIA) discussed their big data and analytics predictions for 2014 in separate webcasts last week. Here is my summary of their predictions plus a few nuggets from other sources. IDC predicts...

Rexer Analytics 2013 Data Miner Survey Highlights

 Top 5 most used tools were R (used by 70% of data miners), IBM SPSS Statistics, Rapid Miner, SAS, and Weka, while STATISTICA, KNIME, SAS JMP, IBM SPSS Modeler, and RapidMiner had the the highest satisfaction. Big...

Using Big Data to Prevent Fraud

 The financial services industry will begin making significant strides in 2014 toward using data analytics to fight fraud, experts predict. The value of using big data to help prevent or detect fraud is becoming clearer, helping institutions...

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