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Data Science Interview Questions and Answers

Basic Data Science Interview Questions and Answers for beginners which would be useful for anyone who is preparing for Data Science Interviews.

For any help on Data Science Certification Training.

What are the important skills to have in Python with regard to data analysis?

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Python or R – Which one would you prefer for text analytics?

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Which technique is used to predict categorical responses? 

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What is the difference between supervised and unsupervised machine learning?

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What is sampling? How many sampling methods do you know?

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What is the difference between type I vs type II error?

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What is linear regression? What do the terms p-value, coefficient, and r-squared value mean? What is the significance of each of these components?

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What is exploding gradients ?

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What is selection Bias ?

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What are the different kernels functions in SVM ?

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What is pruning in Decision Tree ?

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What is Ensemble Learning ?

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What is Random Forest? How does it work ?

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How is Data modeling different from Database design?

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What is logistic regression?

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What are Recommender Systems?

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What is the goal of A/B Testing?

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What do you understand by statistical power of sensitivity and how do you calculate it?

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What are the assumptions required for linear regression?

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What is a statistical interaction?

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What cross-validation technique would you use on a time series dataset?

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What is deep learning?

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What is the difference between machine learning and deep learning?

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Why data cleaning plays a vital role in analysis? 

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Differentiate between univariate, bivariate and multivariate analysis.

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What is Interpolation and Extrapolation?

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What is power analysis?

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What is Collaborative filtering?

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What is the difference between Cluster and Systematic Sampling?

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What is Systematic Sampling?

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What are Eigenvectors and Eigenvalues?

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Can you explain the difference between a Validation Set and a Test Set?

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What does P-value signify about the statistical data?

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Do gradient descent methods always converge to same point?

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What is Supervised Learning?

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What is Unsupervised learning?

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How can you assess a good logistic model?

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What are various steps involved in an analytics project?

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How can outlier values be treated?

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How can you generate a random number between 1 – 7 with only a die?

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What are Artificial Neural Networks?

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Describe the structure of Artificial Neural Networks?

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Explain Gradient Descent?

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What is Back Propagation?

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What are the variants of Back Propagation?

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What are the different Deep Learning Frameworks?

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What is an Auto-Encoder? 

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