Businesses are ultimately still at an early stage with their machine learning adoption and understanding its capabilities. Nikhil Garg, Software Engineering Manager at Quora, for one, notes that “most would agree that the single biggest bottleneck for all machine learning is software engineering. We all collectively in the tech industry are still figuring out the best practices, tools, abstractions, and systems that can enable large organizations to innovate in machine learning at a huge data scale.”
Jérôme Selles, Director of Data Science at Turo, agrees, and argues that overly high expectations could even be damaging. In a recent interview with us, he noted that “when it comes to applications of machine learning, the expectations are usually very high. The full lifecycle of a machine learning project is not necessarily well understood and that can drive disillusion within an organization and for their users.”
Nikhil and Jérôme will be presenting alongside more than 20 other experts from world-leading organizations at the upcoming Machine Learning Innovation Summit, which will take place this June 5-6 at the Marriott Union Square in San Francisco. Speakers from a diverse range of industries take the stage, from retail giants such as Walmart discussing how machine learning is used in inventory management through to Netflix showing how it is used to personalize online content. They will cut through the hype to demonstrate how real businesses can utilize machine learning to their advantage and boost their bottom line.
This event is only in its second year, and with speakers from the likes of Uber and Google, we hope to build on last year’s attendance of 150 to really provide businesses with a greater knowledge and understanding of how they can use machine learning to its full potential,” said Elliot Pannaman, curator of the event.
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