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This article is part of a media partnership with PyData Berlin, a group helping support open-source data science libraries and tools. To learn more about this topic, please consider attending our fourth annual PyData Berlin conference on June 30-July 2, 2017. Miroslav Batchkarov and other experts will be giving talks
Anyone who has ever had their bag go AWOL while travelling knows that sinking feeling that comes with being told that your luggage is lost. Sadly, lost luggage is one of the perils of modern travel, and one that seems to happen on an all-too-often basis. Fortunately, just as technology
Deep learning is a subfield of machine learning and it comprises several approaches to tackling the single most important goal of AI research: allowing computers to model our world well enough to exhibit something like what we humans call intelligence. On a basic conceptual level, deep learning approaches share a
Whilst most businesses don’t earn revenue by processing data, they do spend a large amount of their hard earned revenue in manually processing data, validating it and ultimately performing manual tasks that don’t scale. But at what point does this manual involvement become a burden of cost upon your business?
Big data sets are so complex and large that common data processing tools and technologies cannot cope with them. The process of inspection of such data and uncovering patterns is called big data analytics. The basic question which arises in our mind is, “In what way is the drug discovery
This article is part of a media partnership with Data Analytics and Behavioural Science Applied to Retail and Consumer Markets conference, an event featuring high quality case studies, networking sessions and discussions full of insights on the Retail and Consumer Markets. It takes place June 28 at Millennium Hotel Mayfair, London. To learn more
Artificial Intelligence, Machine Learning and Sentiment Analysis are changing the way in which numerous client services are offered. In particular, Financial Organisations are creating and leveraging such innovation in the domain of wealth management, while academia, start-ups, and technology companies are creating novel and disruptive applications, particularly in the field
Technological innovations have the greatest success in business when they are entirely ‘client- focused’. Developments in the retail sector, which is consumer-led, are addressing client demand for more personalised, faster and more competitive services. Data Analytics is changing the way in which these services are offered. This trend is now