Data Science Interview Questions | Data Science Interview Questions and answers

Data Science Interview Questions list for experienced

What are the differences between supervised and unsupervised learning?
How is logistic regression done?
Explain the steps that are there in making a decision tree?
what is a random forest model?
How to build a random forest model?
How can we avoid the over-fitting of our model?
Differentiate between uni variate ,bi variate and multivariate analysis.

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What is Data Science ?

Answer : Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. Data Science is primarily used to make decisions and predictions making use of predictive causal analytics, prescriptive analytics (predictive plus decision science) and machine learning.

Questions : 1 :: What are the differences between supervised and unsupervised learning?

answer- a supervised learning uses known and labelled data as input,it has a feedback mechanism and is most commonly used learning algorithms are decision tree,logistics ,regression and support...View answers

Questions : 2 :: How is logistic regression done?

Answer- logistic regression measures the relationship between the dependent variable and one or more independent variable by estimating probability using its underlying logistic...View answers

Questions : 3 :: Explain the steps that are there in making a decision tree?

answer- 1.Take the whole data set as the input. 2.calculate entropy of the target variable as well as teh predictor attributes. 3.calculate your information gain of all attributes. 4.choose the...View answers

Questions : 4 :: what is a random forest model?

a random forest model is built up of a number of decision trees .If we split the data into different packages and make a decision tree in each of the different groups of data ,the random forest...View answers

Questions : 5 :: How to build a random forest model?

steps to build a random forest model- 1.Randomly select 'k' features from a total of'm' features where k<<m 2.Among the'k' features ,calculate the node D using the best split point. 3.Split...View answers

Questions : 6 :: How can we avoid the over-fitting of our model?

Overfitting refers to a model taht is only set for a very small amount of data and ignores the bigger picture .There are 3 main methods to avoid overfitting- 1.Keep the model simple- only take few...View answers

Questions : 7 :: Differentiate between uni variate ,bi variate and multivariate analysis.

Univariate- it contains only one variable.The purpose of the univariate analysis is to describe the data and find patterns that exist within it. Bivariate- it involves two different...View answers

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Data Science Interview Questions And Answers