41⟩ Tell me what are the types of biases that can occur during sampling?
☛ Selection bias
☛ Under coverage bias
☛ Survivorship bias
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55 Data Scientist Questions And Answers
42⟩ Tell me do gradient descent methods always converge to same point?
No, they do not because in some cases it reaches a local minima or a local optima point. You don’t reach the global optima point. It depends on the data and starting conditions
43⟩ Tell me what is Linear Regression?
Linear regression is a statistical technique where the score of a variable Y is predicted from the score of a second variable X. X is referred to as the predictor variable and Y as the criterion variable.
44⟩ What is selective bias?
Selection bias, in general, is a problematic situation in which error is introduced due to a non-random population sample.
45⟩ Tell me what is the Law of Large Numbers?
It is a theorem that describes the result of performing the same experiment a large number of times. This theorem forms the basis of frequency-style thinking. It says that the sample mean, the sample variance and the sample standard deviation converge to what they are trying to estimate.
46⟩ Tell me Python or R – Which one would you prefer for text analytics?
The best possible answer for this would be Python because it has Pandas library that provides easy to use data structures and high performance data analysis tools.
47⟩ Do you know what are feature vectors?
A feature vector is an n-dimensional vector of numerical features that represent some object. In machine learning, feature vectors are used to represent numeric or symbolic characteristics, called features, of an object in a mathematical, easily analyzable way.
48⟩ Tell me what is Collaborative filtering?
The process of filtering used by most of the recommender systems to find patterns or information by collaborating viewpoints, various data sources and multiple agents.
49⟩ Please explain what are Recommender Systems?
Recommender systems are a subclass of information filtering systems that are meant to predict the preferences or ratings that a user would give to a product.
50⟩ Tell me what are Recommender Systems?
A subclass of information filtering systems that are meant to predict the preferences or ratings that a user would give to a product. Recommender systems are widely used in movies, news, research articles, products, social tags, music, etc.
51⟩ Tell me what are Eigenvalue and Eigenvector?
Eigenvectors are for understanding linear transformations. In data analysis, we usually calculate the eigenvectors for a correlation or covariance matrix. Eigenvalues are the directions along which a particular linear transformation acts by flipping, compressing or stretching.
52⟩ Do you know what are confounding variables?
These are extraneous variables in a statistical model that correlate directly or inversely with both the dependent and the independent variable. The estimate fails to account for the confounding factor.
53⟩ Explain me what is Interpolation and Extrapolation?
Estimating a value from 2 known values from a list of values is Interpolation. Extrapolation is approximating a value by extending a known set of values or facts.
54⟩ Tell us what is Collaborative Filtering?
The process of filtering used by most recommender systems to find patterns and information by collaborating perspectives, numerous data sources, and several agents.
55⟩ What is survivorship bias?
It is the logical error of focusing aspects that support surviving some process and casually overlooking those that did not because of their lack of prominence. This can lead to wrong conclusions in numerous different means.
