Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...
Today’s AI Won’t Radically Transform Society, But It’s Already Reshaping Business
 Originally published in Fast Company, Jan 5, 2024. Eric...
A University Curriculum Supplement to Teach a Business Framework for ML Deployment
    In 2023, as a visiting analytics professor...
The AI Playbook: Providing Important Reminders to Data Professionals
 Originally published in DATAVERSITY. This article reviews the new...

data science

How to Harness Predictive Analytics and Become a Big Data Dynamo

 Predictive analytics has come a long way and, in an era defined by the ever-increasing influx of data and heightened customer demands, businesses no longer can deny its strategic importance. Industries such as insurance, financial services, and retail have used predictive analytics for decades, while others are just getting started. So what’s new? Predictive analytics

Netflix, Dark Knowledge, and Why Simpler Can Be Better

 Weary from an all-night coding effort, and rushed by the looming 6:42PM deadline, Lester Mackey searched franticly for the proper prediction file to submit. Lester was a member of “The Ensemble”—a large coalition of data scientists who...

Changing the Retail Sector with Big Data

 Big Data analytics is now being applied at every stage of the retail process – working out what the popular products will be by predicting trends, forecasting where the demand will be for those products, optimizing pricing...

The Ultimate Guide to Data Science Blogs

 We’ve organized data science blogs across eight different categories: Machine learning, Hadoop, R, Python, business intelligence, data visualization, statistics, and a general data science bucket. Data about their reader count comes from Feedly. This is a work...

B2B Predictive Analytics: An Untapped Sector

 Much work in predictive analytics and data science has been primarily focused around the business to consumer sector (B2C). Certainly predictive analytics solutions have been applied to the B2B sector but it pales in comparison to what...

4 Reasons Why Healthcare Needs Data Science

 The amount of healthcare data continues to mound every second, making it harder and harder to find any form of helpful information. In the healthcare industry, what could be more important than having better healthcare outcomes? Each...

Four Ways Data Science Goes Wrong and How Test-Driven Data Analysis Can Help

 If, as Niels Bohr maintained, an expert is a person who has made all the mistakes that can be made in a narrow field, we consider ourselves expert data scientists.  After twenty years of doing what’s been...

Getting More Value from Data: 6 Facts About Data Science

 The value of data is measured by what you do with it, and organizations are relying on data scientists to extract that value. I recently conducted a survey of data professionals to better understand what it means...

The Hardest Parts of Data Science

 Contrary to common belief, the hardest part of data science isn’t building an accurate model or obtaining good, clean data. It is much harder to define feasible problems and come up with reasonable ways of measuring solutions....

Analysts with Superpowers

 USE CODE PATIMES16 for 15% off Predictive Analytics World Conference pass. Imagine that you are a business analyst who works for an organization with executives, managers and colleagues who do not appreciate the power of analytics to...

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