Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...

Industry News

Understanding Your Business With Descriptive, Predictive And Prescriptive Analytics

 Companies have long been involved in the analysis of how a company performed over time. As the history of big data shows, already for many years we try to understand how the organisations or the world around us behaves by analysing the available data. In the past this used to be merely descriptive analytics. This

“The hungry statistician” – or why we never can get enough data

 As the “Year of Statistics” comes to a close, I write this blog in support of the many statisticians who carefully fulfil their analysis tasks day by day, and to defend what may appear to be demanding behavior when...

Analytics 3.0 — the old guard masters how to build data products

 Asked to name a big data company, many of us would say Google or Facebook or eBay. But for old-school giants such as General Electric Co. and Macy’s Inc., big data is fast becoming as central to...

Data Science Wars: Python vs. R

 As I frequently travel in data science circles, I’m hearing more and more about a new kind of tech war: Python vs. R. I’ve lived through many tech wars in the past, e.g. Windows vs. Linux, iPhone...

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...

Predictive Analytics, a game changer for transaction banking

 Transaction banking has made huge strides in recent years. The easy availability of new technologies has improved operating efficiencies and accuracy. Apart from this, the speed of transactions has also increased remarkably. The volume of transaction banking...

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...

Using Analytics to Crack Down on Electricity Theft

 Electricity theft is estimated to cost the energy industry approximately $6 billion each year. Analytics can help them recoup a significant portion of those losses. People go to all kinds of lengths to steal electricity. Some simply...

3 Ways That Predictive Analytics Help Travel Companies Improve Planning

 While heaps of big data exist in the travel sector – from how seasonality affects bookings to the types of travel packages that receive the highest conversion rates among consumers – leveraging some of the more unstructured...

Predictive Analytics World founder explains how uplift modeling works

 Watch the interview with the PAW Founder, Eric Siegel. In the opening keynote session at the 2013 Predictive Analytics World conference in Boston, only two attendees raised their hands when speaker Eric Siegel asked how many people...

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