In 2016, Google’s net worth was reported to be $336 billion, and this is largely due to the advanced learning algorithms the company employs. Google was the first company to realize the importance of incorporating machine learning in business processes. And the technology powerhouse doesn’t stop at any given point; it keeps

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Linear regression is a basic tool. It works on the assumption that there exists a linear relationship between the dependent and independent variable, also known as the explanatory variables and output. However, not all problems have such a linear relationship. In fact, many of the problems we see today are

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Big data has rapidly made its way into a wide range of industries. Healthcare is ripe for big data initiatives—as one of the largest and most complex industries in the United States, there is an incredible number of potential applications for predictive analytics. While some healthcare organizations have begun to

The post 5 Ways The Healthcare Industry Could Use Big Data—and Why It’s Not appeared first on Dataconomy.

Big data and sports analytics are changing the ways many things in sports have traditionally been done. They are allowing for new processes that have the potential to alter the way that organizations conduct their scouting. This is because data science and sports analytics are opening up new data points

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One of the great things about running a startup is that you’re working with a clean slate. If you have worked with a different organization before, you may have had issues with culture and people that you probably don’t want happening with your own company. Existing organizations, especially the established

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Introduction A couple of months ago a client of mine asked me the following question: “What is the faster data structure object in Python for Big Data analysis today?” I get questions like this one all the time. Some of them are not easy to solve at all and it

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