Explainability of predictive models

Why is Explainability important and how can it be achieved?

By law, organisations must take accountability for how they are using and processing data. Exlainability is key to this. Picture ...
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data scientists should consider

Five important considerations for Data Scientists

Data science as a strategic business tool is growing in prominence.It is not surprising that a recent study by Deloitte ...
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Changing Consumer

Keeping up with the customer

"This year two types of business change are deemed important – the speed of technological change and the changing consumer." ...
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Lara Korz, Azur

Data science gives a competitive advantage by delivering a better customer experience

Data science is giving Azur a competitive advantage by delivering a better customer experience. With Lara Korz - Chief Data Officer, ...
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digital transformation to data transformation

From Digital Transformation to Data Transformation

Fifteen years ago there was much debate about the chasm that existed between marketing and IT. This gap took the ...
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Data Provenance and Ethics

Is Data Provenance and Ethics one of Your Corporate New Year’s Resolutions? If Not, It Should Be!

2018 and the introduction of GDPR seems to be a fading memory for many based on what I see as ...
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Six factors for modelling with confidence in 2019

Find out why Confidence Scores will become increasingly important in 2019.In the marketing arena the increased use of big data ...
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insurance industry

The pragmatic applications of AI in the Insurance Industry

Increasingly artificial intelligence and deep learning are hitting the headlines. Recently it was reported that IBM has created a secret ...
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Year Ahead: Get set for the rise of nano-segmentation

Segmenting people into groups based on something they have in common has been around since the 16th Century – Yeomans, ...
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