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Data Science Interview Questions
Questions Answers Views Company eMail

Define the term cross-validation

308

what the aim of conducting a/b testing?

323

What is the k-means clustering method?

368

Name various types of deep learning frameworks

423

State the difference between the expected value and mean value?

338

Explain auto-encoder

320

How do you overcome challenges to your findings?

354

Discuss normal distribution

380

Explain cluster sampling technique in data science

399

What is the importance of having a selection bias?

312

Explain the steps for a data analytics project

439

Treating a categorical variable as a continuous variable would result in a better predictive model?

322

Name three types of biases that can occur during sampling?

324

What is a recall?

372

Explain the method to collect and analyze data to use social media to predict the weather condition?

537


Post New Data Science Questions

Un-Answered Questions { Data Science }

Define linear regression?

321


How does data cleaning plays a vital role in the analysis?

383


Is it possible to capture the correlation between continuous and categorical variable?

321


When underfitting occurs in a static model?

390


How do data scientists code in r?

331


Define naive bayes?

307


Differentiate between data modeling and database design?

320


What is random forests and how is it different from decision trees?

303


Can you cite some examples where a false positive is important than a false negative?

359


What are the various classification algorithms?

347


During analysis, how do you treat missing values?

402


What do you understand by ensemble learning?

346


Name the methods for General component analysis and explain them?

386


How would churn help predict and control churn for a customer?

293


Can you cite some examples where both false positive and false negatives are equally important?

393