EP33b: Machine learning is not a magic box that takes data and gives magic findings — An Interview with Drew Conway of Alluvium
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Where within the chain of operation in an industrial company is the best place to insert a piece of software? Is a bus system just a bunch of big computers moving around on wheels? Does machine learning hold the answer to maximising the value of each interaction between humans and software? Are we all data engineers regardless of what our name card states?
Drew explains how to take heterogenous data streams and distill it into a stability score that is an index of operations and produce high value alerts. We also explore human machine interaction to build a model more effectively than a fully unsupervised method.
Drew Conway is the CEO and founder of Alluvium. Alluvium is a data company. Alluvium uses machine learning and artificial intelligence to turn massive data streams produced by industrial operations into insights that help you, the experts, focus on the anomalies that affect your team’s safety, productivity and bottom line. http://www.alluvium.io
IoT ONE is an online platform devoted to accelerating adoption of Industrial Internet solutions. We are mapping the global ecosystem of IoT vendors, use cases, case studies, and technologies. We leverage this data to help companies source technology, research competitors, and enter new markets.
Learn more about IoT One: https://www.iotone.com