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

Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Chris Labbe at Seagate Technology

 In anticipation of his upcoming Predictive Analytics World for Manufacturing conference presentation, Building a Predictive Analytics Organization, we interviewed Chris Labbe, Managing Technologist at Seagate Technology. View the Q-and-A below for a glimpse of what’s in store at the PAW Manufacturing conference. Q: What are the challenges in translating the lessons of predictive analytics from other verticals into manufacturing?

Feature Engineering within the Predictive Analytics Process — Part One

 What is Feature Engineering One of the growing discussions and debates within the data science community is the determination of inputs or variables that should be included in any predictive analytics algorithm. This type of process is...

Wise Practitioner – Predictive Analytics Interview Series: Lawrence Cowan at Cicero Group

 In anticipation of his upcoming conference presentation, Data Driven Selling: Enabling a Direct Salesforce with Tools that Re-Enforce Predictive Selling Methods at Predictive Analytics World Chicago, June 20-23, 2016, we asked Lawrence Cowan, Partner at Cicero Group,...

Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Gary Neights at Elemica

 In anticipation of his upcoming Predictive Analytics World for Manufacturing conference presentation, Analytics in Manufacturing Supply Chains – Predicting Behavior In Chemical Industry Supply Chains, we interviewed Gary Neights, Senior Director at Elemica. View the Q-and-A below for a glimpse of...

Wise Practitioner – Manufacturing Predictive Analytics Interview Series: Jeffrey Banks at The Applied Research Laboratory at The Pennsylvania State University

 In anticipation of his upcoming Predictive Analytics World for Manufacturing conference presentation, Using Vehicle Digital Bus Data for Predicting Failure of Line Haul Trucks, we interviewed Jeffrey Banks, Department Head, Complex Systems Engineering & Monitoring at The Applied Research Laboratory...

Wise Practitioner – Predictive Analytics Interview Series: Alice Chung at Genentech

 In anticipation of her upcoming conference co-presentation, Utilizing Advanced Analytics to Generate Insights at Predictive Analytics World Chicago, June 20-23, 2016, we asked Alice Chung, Senior Manager at Genentech, a few questions about her work in predictive...

How Stubby Datasets Can Lead to Predictive Analytics Snafus

 Here’s a question for PATIMES members interested in Big Data and predictive analytics to ponder: “When is bigger data more hazardous?” And, here’s an answer to puzzle over: “When it is wider.” Eric Siegel, executive editor of...

Share your Insights at Text Analytics World

  You’re invited! We’re reaching out to request that you submit a speaker proposal for Text Analytics World Hilton Chicago  |  June 21-22, 2016 Deadline: Friday, February 19, 2016 If you’re capturing business value from unstructured text...

The Big Data Gold Rush

 A 21st century gold rush is under way — but it isn’t about precious metal, it’s about data. The amount of information coming from digital sources such as blogs, social media, databases, audio, and video continues to...

Predictive Analytics and the Internet of Things

 As technology continues to empower our ability to conduct analytics with “Big Data”, the “Internet of Things” has arisen as an area where devices themselves capture and transmit data albeit machine-level type data. Let’s discuss some of...

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