Q. Differences between overfitting and underfitting ?
A. In statistics and machine learning, individual of that most basic tasks is to fit one model on a collection of training data, so doing to be ready to provide reliable predictions of general untrained data.
Underfitting happens at a statistical design or machine learning algorithm cannot get this underlying trend of the data.
Q. What is univariate analysis ?
A. Univariate analyses are detailed statistical analysis methods which can be changed based upon the number of variables involved in a distributed period of time.
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Q. What is bivariate analysis ?
A. The bivariate analysis tries to explain that difference between two variables at an individual time as in a scatterplot.
Q. What is multivariate analysis in Data Science?
A. Multivariate analysis contracts including the single study from and then a couple of variables to understand the effect from variables to some responses
Q. Differentiate between univariate, bivariate and then multivariate analysis ?
A. Univariate analyses are detailed statistical analysis methods which can be changed based upon the number of variables involved in a distributed period of time.
The bivariate analysis tries to explain that difference between two variables at an individual time as in a scatterplot.
Multivariate analysis contracts including the single study from and then a couple of variables to understand the effect from variables to some responses.
Q. What is the memory limit of R in data science?
A. In 32 bit system memory limit is 3Gb but most versions limited to 2Gb and in 64 bit system memory limit is 8Tb.
Q. What do you know by the term Normal Distribution?
A. Data is usually distributed under many ways including a bias on the port or over the benefit or it can all be jumbled up.
However, there continue indications that data is distributed on a central position without bias to the left or right more gives natural order in some form of a bell-shaped curve.
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