Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Survey: Machine Learning Projects Still Routinely Fail to Deploy
 Originally published in KDnuggets. Eric Siegel highlights the chronic...
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,...

Left-hand

How Machine Learning Pushes Us to Define Fairness

 Originally published in Harvard Business Review, November 6, 2019. Bias is machine learning’s original sin. It’s embedded in machine learning’s essence: the system learns from data, and thus is prone to picking up the human biases that the data represents. For example, an ML hiring system trained on existing American employment is likely to “learn”

A.I. Is Learning From Humans. Many Humans.

 Originally published in The New York Times, August 16, 2019. BHUBANESWAR, India — Namita Pradhan sat at a desk in downtown Bhubaneswar, India, about 40 miles from the Bay of Bengal, staring at a video recorded in...

Data Lakes: The Future of Data Warehousing?

 Originally published in InsideBigData, August 2, 2019. The term Big Data has been around since 2005, but what does it actually mean? Exactly how big is big? We are creating data every second. It’s generated across all...

10 Great Python Resources for Aspiring Data Scientists

  Originally published in KDNuggets, September 10, 2019 Python is one of the most widely used languages in data science, and an incredibly popular general programming language on its own. Many prospective data scientists are first faced...

Machine Learning You Can Dance To

  Originally published in MIT News, September 18, 2019. Rhythmic flashes from a computer screen illuminate a dark room as sounds fill the air. The snare drum sample comes out crisp and clean by itself, but turns...

Top 10 Data Science Use Cases in Energy and Utilities

 Originally published in KDNuggets, September, 2019. The energy sector is under constant development, and more of significant inventions and innovations are yet to come. The energy use has always been involved in other industries like agriculture, manufacturing,...

Machine Learning in Auditing – Current and Future Applications

  Originally published in The CPA Journal, June, 2019. Machine learning is a key subset of artificial intelligence (AI), which originated with the idea that machines could be taught to learn in ways similar to how humans...

An Easy Introduction to Machine Learning Recommender Systems

  Originally published in KDNuggets, September, 2019. Recommender systems are an important class of machine learning algorithms that offer “relevant” suggestions to users. Categorized as either collaborative filtering or a content-based system, check out how these approaches...

What Happened to Hadoop? And Where Do We Go from Here?

 Originally published by InsideBigData, September 4, 2019. Apache Hadoop emerged on the IT scene in 2006 with the promise to provide organizations with the capability to store an unprecedented volume of data using cheap, commodity hardware. In...

The Death of Big Data and the Emergence of the Multi-Cloud Era

 Originally published in KDnuggets, July, 2019 The Era of Big Data is coming to an end as the focus shifts from how we collect data to processing that data in real-time. Big Data is now a business...

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