Digital Newsletter
Each week our editor Phil Alsop rounds up the most popular articles, videos and expert opinions. We compile this into a Digital Newsletter and send it straight to your inbox every week.
Digital Magazines
We'll let you know each time a new edition of Digitalisation World is released so that you're always kept up-to-date with the latest and greatest news and press releases.
Video Magazines
The Digitalisation World Video magazine contains the latest Zoom interviews with experts in the industry.
By Rachel Roumeliotis, VP of Data and AI at O’Reilly.
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Building ML Models may be ‘Data Fun’ but using them to support the business is where the value lies. By John Spooner, Head of Artificial Intelligence, EMEA, H2O.ai.
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DW/DCS talks to Richard Clifford, Head of Innovation at Keysource, about the launch of a new facilities maintenance service - Keysource Artificial Intelligence (KAI) - which uses machine learning and artificial intelligence technology to help organisations transform their edge operational management strategy.
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These days, data is viewed as the lifeblood of organisations. Gartner has been heavily focused on the importance of developing a data-driven culture in the past year, stating that: “Leaders need to cultivate an organisational culture that is data-literate and that values information as an asset.” By Matt Middleton-Leal, EMEA & APAC General Manager at Netwrix.
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On this podcast edition, Eric Nielsen, Sr. Director Social Media & Communities and his Co-host: John White, Systems Engineer, will have a roundtable discussion w/ Justin Murray, VMware Technical Marketing Architect to talk about Machine Learning on vSphere
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UiPath robots can leverage Machine Learning to gain skills. This demo shows a robot that learned to read receipts and create expenses in Concur.
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Hear LinkedIn’s senior SRE, Todd Palino, share how the company continually improves the state of its infrastructure, so that the developers who are rolling out applications have a framework that they can do it within, and they can do it safely. LinkedIn currently generates over 50 terabytes a day of unique metrics on applications. No human is going to look at 50 terabytes a day of data and get anything useful out of it, so LinkedIn relies on systems give them some useful signal out of all that noise. By moving down the road of machine learning, LinkedIn can now do anomaly detection using machine learning models.
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