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Data Science 101

BI & AnalyticsBig DataData ScienceData Science 101EducationFeatured

Data professionals across industries recognize they must effectively harness data for their businesses to innovate and gain competitive advantage. High quality, reliable data forms the backbone for all successful data endeavors, from reporting and analytics to machine learning. Delta Lake is an open-source storage layer that solves many concerns around data

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Data ScienceData Science 101EducationFeatured

If you are a developer or data scientist interested in big data, Spark is the tool for you. Apache Spark’s ability to speed analytic applications by orders of magnitude, its versatility, and ease of use are quickly winning the market. With Spark’s appeal to developers, end-users, and integrators to solve

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ContributorsData ScienceData Science 101FeaturedTech Trends

Data Science is described as “the career of the future,” but finding Data Scientists for your company could be a major challenge. Here is how you could find one for your company. As demand keeps growing for people with the expertise to manage, analyze and safely store ever-larger sets of

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Artificial IntelligenceData NativesData Science 101EducationEventsFeaturedInterviewsMachine LearningTech TrendsTechnology & IT

AI has been facing a PR problem. Too often AI has introduced itself as a misogynist, racist and sinister robot. Remember the Microsoft Twitter chatbot named Tay, who was learning to mimic online conversations, but then started to blur out the most offensive tweets? Think of tech companies creating elaborate

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Big DataData NativesData ScienceData Science 101FeaturedTech Trends

The success of data-driven projects has quite a few challenges and barriers. Here is a look at how you could overcome them by simply asking yourself three questions. Data has become probably the most valuable asset that companies could have nowadays. It can give you insights into your customers’ behaviour

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Nonlinear Regression
Data ScienceData Science 101Resources

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 DataData Science 101Understanding Big Data

This article is a continuation of my first article, 25 Big Data terms everyone should know. Since it got such an overwhelmingly positive response, I decided to add an extra 50 terms to the list.  Just to give you a quick recap, I covered the following terms in my first

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Data ScienceData Science 101Resources

In recent years’ evidence has been mounting that points to a crisis in the reproducible results of scientific research. Reviews of papers in the fields of psychology and cancer biology found that only 40% and 10%, respectively, of the results, could be reproduced. Nature published the results of a survey of

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Data ScienceData Science 101Machine Learning

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

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Data ScienceData Science 101Resources

The R language is often perceived as a language for statisticians and data scientists. Quite a long time ago, this was mostly true. However, over the years the flexibility R provides via packages has made R into a more general purpose language. R was open sourced in 1995, and since

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