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Data Science Interview Questions
Questions Answers Views Company eMail

What makes the difference between “long” and “wide” format data?

288

How and by what methods data visualizations can be effectively used?

303

How regularly must an algorithm be updated?

328

How often should an algorithm be updated?

286

What prior subject is required to become a data analyst?

290

How do you define data science?

286

How have you overcome a barrier to finding a solution?

265

Why is data cleaning essential in data science?

266

What is cross-validation?

266

What is meant by selection bias?

335

List the variants of backpropagation?

336

What are eigenvectors and eigenvalues?

376

Now companies are heavily investing their money and time to make the dashboards. Why?

286

What are an eigenvalue and eigenvector?

286

What are outlier values and how do you treat them?

342


Post New Data Science Questions

Un-Answered Questions { Data Science }

Differentiate between supervised and unsupervised learning?

262


Can you compare the validation set with the test set?

296


Are expected value and mean value different?

382


How do you treat outlier data?

303


What do I need to study to become a data analyst?

287


What packages are used for data mining in python and r?

309


How can you compare a neural network that has one layer, one input and output to a logistic regression model?

262


How will you overcome overfitting in predictive models?

388


What is cart and chaid?

287


What do you understand by ensemble learning?

314


How can I achieve accuracy in the first model that I built?

262


How can you build and test a metric to compare ranked list of TV shows or Movies for two Netflix users?

526


Explain root cause analysis?

309


List the variants of backpropagation?

336


How is true positive rate and recall related?

255