Examples of using Data scientists in English and their translations into Serbian
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Colloquial
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Ecclesiastic
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Computer
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Latin
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Cyrillic
Data scientists are generally excited;
But, companies large and small need more than data scientists;
Data scientists are generally excited;
These are two of the key characteristics of excellent data scientists.
And that puts data scientists in a prime position.
This second group resists an easy name, butI will call them data scientists.
Data scientists: we should not be the arbiters of truth.
This second group resists an easy name, butI will call them data scientists.
Many data scientists see a cool new machine learning problem.
Thus, social research will be shaped by both social scientists and data scientists.
Many data scientists see a cool new machine learning problem.
In my experience,social scientists and data scientists approach to this repurposing very differently.
Data scientists are in short supply but in demand by many industries.
Thus, social research will be shaped by both social scientists and data scientists.
Data scientists are going to be among the most demanded specialists on the hi-tech market.
There are important differences between how social scientists and data scientists approach research ethics.
Data scientists, however, have less training and experience studying social behavior.
The second main solution is to do what data scientists call user-attribute inference and social scientists call imputation.
Data scientists might call these characteristics“features” and social scientists would call them“variables.”.
Second, there is a concern that in the future,there will only be room for engineers, data scientists, and other highly-specialized workers.
Many choose careers as data scientists, some focusing on computer science while others prefer to work on analytics.
As such, Dunn expressed his optimism that the token will now benefit those it is intended to serve- the data scientists helping to improve the outcome of its trading.
Data scientists might call these characteristics“features” and social scientists would call them“variables.”.
The second main solution is to do what data scientists call user-attribute inference and social scientists call imputation.
Data scientists and software engineers are two different fields, but that doesn't necessarily mean overlap doesn't happen.
This master in data science will provide data scientists with the skills needed to be productive in a world of data and‘big data'.-.
Data scientists have the analytical and programming skills needed to extract valuable knowledge out of data. .
This contrast also captures a difference between data scientists, who tend to work with Readymades, and social scientists, who tend to work with Custommades.
Data scientists, on the other hand, have little systematic experience with research ethics because it is not commonly discussed in computer science and engineering.
The study predicted a shortfall by 2018 of nearly 200,000 data scientists and 1.5 million managers with the capability to make decisions using big data in the United States alone.