Walmart – Data Scientist Interview Questions
Here is the list Data Science Interview Questions which are recently asked in Walmart company. These questions are included for both Freshers and Experienced professionals. Our Data Science Training has Answered all the below Questions.
- Write the code to reverse a Linked list.
- What assumptions does linear regression machine learning algorithm make?
- A stranger uses a search engine to find something and you do not know anything about the person. How will you design an algorithm to determine what the stranger is looking for just after he/she types few characters in the search box?
- How will you fix multi-colinearity in a regression model?
- What data structures are available in the Pandas package in Python programming language?
- State some use cases where Hadoop MapReduce works well and where it does not.
- What is the difference between an iterator, generator and list comprehension in Python?
- What is the Law of Large Numbers?
- What is A/B testing in Data Science?
- What are the differences between overfitting and underfitting?
- What is collaborative filtering?
- Explain Star Schema?
- What is the difference between a bagged model and a boosted model?
- What do you understand by parametric and non-parametric methods? Explain with examples.
- Have you used sampling? What are the various types of sampling have you worked with?
- Explain about cross entropy ?
- What are the assuptions you make for linear regression ?
- Differentiate between gradient boosting and random forest.
- What is the signigicance of log odds ?
- What is a Linear Regression?
- How do you define data science?
- What are Eigenvalue and Eigenvector?
- What is a Random Forest?
- What is power analysis?
- Do gradient descent methods always converge to same point?
TOP MNC's DATA SCIENCE INTERVIEW QUESTIONS & ANSWERS
Here we listed all Data Science Interview Questions and Answers which are asked in Top MNCs. Periodically we update this page with recently asked Questions, please do visit our page often and be updated in Data Science.
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