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.
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.
Frequently Asked Data Science Interview Questions And 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.
Q41. What is a nonparametric test used for?
Q42. What are the pros and cons of Decision Trees algorithm?
- Pros : Easy to interpret
- Will ignore irrelevant in dependant variable's minimal.
- Can handle missing data. Fast modelling.
There are chances that it might not find the best tree possible.
Q43. Name some Classification Algorithms.
- Linear Classifiers:
- Logistic Regression,
- Naive Bayes Classifier,
- Decision Trees,
- Random Forest,
- Neural Networks,
- K Nearest Neighbor.
Q44. What are pros and cons of Naive Bayes algorithm?
Pros: Big sized data is handled easily
Multiclass perfomance is good and accurate
It is not process intensive
Cons: Assumea independence of predictor variables.
Q45. What is skewed data?
Q46. What is an outlier?
Q47. What are the applications of data science?
- Optical character recognition,
- recommendation engines,
- filtering algorithms,
- personal assistants,
- advertising,
- surveillance,
- autonomous driving,
- facial recognition and more.
Q48. What is an EDA?
EDA [exploratory data analysis] is an approach to analyzing data to summaries their main characteristics, often with visual methods.
Q49. What are the steps in exploratory data analysis?
- Make summary of observations
- describe central tendencies or core part of datasets
- describe shape of data
- identify potential associations
- develop insight into errors, missing values and major deviations
Q50. What are the types of data available in Enterprises?
- Structured data
- unstructured data
- big data from social media,
- surveys,
- pictures,
- audio,
- video,
- drawings, maps.
- Machine generated data from instruments
- real time data feeds
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