Machine Learning System Detects Manufacturing Defects Using Photos
Machine learning can be used for more than violating your privacy for a social media challenge. For example, one fascinating application has been develope
Machine learning can be used for more than violating your privacy for a social media challenge. For example, one fascinating application has been develope
Counterfeiting is widespread and rapidly expanding. In 2015, the value of fake and pirated products globally was estimated at $1.7 trillion, equivalent to the GDP of Canada. The scope of this phenomenon is vast.
Responsibility. It’s a hard word to come to grips with. What is the responsible thing to do right now? What is my personal responsibility? What is my responsibility as a team, family, company, state, or country member? What do I expect from others?
After reviewing Mark Graban’s wonderful book, Measures of Success (Constancy, 2018), I started rereading Walter Shewhart’s books,
How do you develop domain knowledge in your analysts, so their data use, interpretation, and recommendations make sense?
While I was facilitating a retreat for a group of 15 men, all in their late 30s and 40s, all high-level executives and all high achievers, an interesting topic arose. One of the men asked for help dealing with his wife, who was complaining he worked too much.
Someone we know recently told us about a team-building event that proved anything but.
Globalization of the medical device market as well as its supporting supply chains continues to increase year after year. This has forced regulatory bodies to grapple with finding a way to narrow the gap between international and domestic regulation.
It happens easily enough and usually innocently enough. You start a business or organization then endure what is often a long and expensive learning curve. Along the way you learn. You learn a lot.
It’s no news that U.S. manufacturing has a workforce problem. However, a new survey conducted by Leading2Lean (L2L) offers some unexpected hope.
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