A guide to machine learning

Machine learning (the subfield of computer science that, according to Arthur Samuel, “gives computers the ability to learn without being explicitly programmed”) is one of the most innovative and interesting fields of modern science around today. Something that you probably associate with things such as Watson, Deep Blue, and even the infamous Netflix algorithm. However, as sparkly as it is, machine learning isn’t exactly something totally new. In fact, the concept and science of machine learning has been around for much longer than you think.

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A Clear Picture

A Clear Picture

IT and business management are increasingly concerned with the rising costs associated with their highly complex and ever-growing mainframe and distributed systems data centers. They are also concerned about controlling outages and mitigating the lack of transparency that they have into cost drivers—including in their outsourced environments.

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Banking Trends

Banking Trends and IT Issues

Digital transformation is impacting businesses far and wide, but you could argue that none are being impacted more dramatically than banking. Over the course of the past few decades the manner in which banks interact with their customers has changed significantly, and more changes are on the horizon.

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3rd platform and the mainframe

The Third Platform and the Mainframe

The Third Platform is defined as the interdependencies between mobile computing, social media, cloud computing, and information/analytics (big data), and possibly the Internet of Things (IoT). Here is a nice rendering of the Third Platform model from Forbes.com. It shows our new concerns: Mobility, Analytics, and Cloud (SMAC-IT) at the top level on the “Third Platform,” our LAN/Internet and our Client/Server apps on the “Second Platform,” and the clunky old Mainframe on the “First Platform.” When talking about the First Platform, people say that we know how these systems worked and how they were used, as if it’s all in the distant past. And that’s a mistake.

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