Data Science Interview Questions with Answers

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 Data Science Interview Questions with Answers listed here by our experts will give you a perfect guide to get through the interviews, online tests, certifications, and corporate exams. To get in-depth knowledge and frequently posted queries of the Data Science topic, just have a glance at the below questionnaire as it will really help both freshers and experienced candidates.

In this Data Science Interview Questions and answers are prepared by 10+ years of experienced industry experts. Data Science Interview Questions and answers are very useful to the Fresher or Experienced person who is looking for a new challenging job from the reputed company.

Best 100+ Data Science Interview Questions with Answers

By this Data Science Interview Questions and answers, many students are got placed in many reputed companies with high package salaries. So utilize our Data Science Interview Questions and answers to grow in your career.

Q1. What is Data Science ?

Answer: Defination 1: Data Science is a combination of algorithms, tools, and machine learning technique which helps you to find common hidden patterns from the given raw data.
Defination 2: Data Science is a bled of mathematics, business awareness, tools, algorithms and machine learning techniques, all of which help us in finding out the hidden data or patterns from raw data which can be of major use in the formations of big business decisions.
Q2.What are the types of machine learning?

Answer:
  • Supervised learning
  • Unsupervised learning
  • Reinforcement Learning
Q3.What are the commonly used python packages?

Answer:
  • Numpy
  • Pandas
  • SCI-KIT Learn
  • Matplot library
Q4. What Is A Recommender System?

Answer: A recommender system is today widely deployed in multiple fields like movie recommendations, music preferences, social tags, research articles, search queries and so on. The recommender systems work as per collaborative and content-based filte ring or by deploying a personality-based approach.
This type of system works based on a person’s past behavior in order to build a model for the future. This will predict the future product buying, movie viewing or book reading by people. It also creates a filtering approach using the discrete characteristics of items while recommending additional items.
Q5.What are the commonly used R packages?

Answer:
  • Caret
  • Data.Table
  • Reshape
  • Reshape2
  • E1071
  • DMwR
  • Dplyr
  • Lubridate
Q6.Name the commonly used algorithms.

Answer:
  • Linear regression
  • Logistic regression
  • Random Forest
  • KNN
Q7.What is precision?

Answer: The ration of predicted positive against the actual positive.
It is the most commonly used error metric is n classification mechanism.
The range is from 0 to 1, where 1 represents 100%.
Q8. What is recall?

Answer: The ratio of the true positive rate against the actual positive rate.
The range is again from 0 to 1
Q9. What is a normal distribution?

Answer: When the data distribution is equally distributed as such the mean, median and mode are equal.
Q10.What is overfitting?

Answer: Any prediction rate which has high inconsistency between the training error and the test error leads ta a high business problem, if the error rate in training set is low and the error rate ithe n test set is high, then we can conclude it as overfitting model.

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