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The buzz around machine learning (ML) has been growing steadily since 2012. But many executives often have trouble identifying use cases where ML can make a real impact. With new AI terminology being created weekly, it can seem difficult to get a hold of what applications are viable, and which are hype, hyperbole, or hoax.

Samir Sharma, the Founder & CEO at Datazuum, is hosting this month's online discussion.
Samir has been kind enough to provide us with a trio of resources for this event outlining his thinking on the challenges faced by businesses that want to adopt machine learning. He also offers some potential solutions to some of the most common issues.

The three articles Samir has shared are listed below. He will be in our community from 11 am on Friday the 31st of May to answer any questions about them.

If you’d like to get involved you can sign up to our Slack group here and head over to the #venturi-live channel: http://bit.ly/samir-data

Machine learning is dead. Long live machine learning.
Is the machine learning boom over before it started? Why has it disappeared from the Gartner ‘hype cycle’? Why is it still worth investing in machine learning in 2019?

The renaissance of data
Is the emphasis on ‘data-driven’ businesses really as new as it seems? Or are we just seeing the next repackaging of the boom and bust data lifecycle? What can your business do to ensure that your data strategy doesn’t become a passing fad?

What are your organization's aspirations for data?
Are we running before we can walk when it comes to data? Has the hype got businesses hiring data experts with no end goal in mind? What can your business do to avoid these pitfalls and create a robust and lasting data strategy?

Sign up to take part here: http://bit.ly/samir-data

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