MCQ Question | Machine learning interview Questions Part 2

Machine Learning interview Questions

Preparing for Machine learning Interview? Don’t be stressed, take our Question on Machine learning based quiz and prepare your self for the interview. 

With this Machine learning Interview Questions, we are going to you build your confidence by providing tips and trick to solve Machine learning interview questions. Here you will get Machine learning MCQ questions General ( Multiple Choice Questions ) and Answers for your next job or exam. In Machine learning MCQ questions based practice tests, there will be a series of practice tests wherein you can test your Basic question on Machine learning concepts on every Topic. 

Who should Practice these Machine learning Interview Questions based? 

• Anyone wishing to sharpen their knowledge in Machine learning 
• Anyone preparing for JOB interview question on Machine learning 

What is the Importance of Machine learning ? 

Machine learning is a revolutionary technology that’s changing how businesses and industries function across the globe in a good way. This Machine Learning interview questions, is a practice test that is focused to help people wanting to start their career in the Machine learning industry. This question on Machine Learning Bootcamp helps you assess how prepared are you for the Job Interview. 

Here, you get Machine Learning MCQ questions that test your knowledge on the technology. These Machine Learning Questions are prepared by subject matter experts and are in line with the questions you can come across in Job Interview. Take this test today! 

Generally, you need to refer a variety of books and Websites in order to cover the ocean of topics in Machine learning. To make it easy for you guys, I have collected a few Machine learning Based questions from different topics, When you solve these Question on machine learning then definitely Your confidence. will Increase. 

What you’ll learn 

• Able to Solve Machine Learning Based Question 

Are there any course requirements or prerequisites? 

• Basic knowledge of mathematics 
• Basic Knowledge of Computer Engineering 
• Basic Knowledge of Programming 

Who this Machine learning interview questions is for: 

• Students will develop a strong confidence on topic, "Machine Learning"

• Which of the factors affect the performance of learner system does not include?

  A. Representation scheme used
  B. Training scenario
  C. Type of feedback
  D. Good data structures
  
  Eplanation
  The Correct Answer is D.
  
  

  Factors that affect the performance of learner system does not include good data structures.

• A model of language consists of the categories which does not include?

  A. Language units
  B. Role structure of units
  C. System constraints
  D. Structural units
  
  Eplanation
  The Correct Answer is D.
  
  

  A model of language consists of the categories which does not include structural units.

• To find the minimum or the maximum of a function, we set the gradient to zero because:

  A. The value of the gradient at extrema of a function is always zero
  B. Depends on the type of problem
  C. Both A and B
  D. None of the Above
  
  Eplanation
  The Correct Answer is A.
  
  

  The value of the gradient at extrema of a function is always zero

• The most widely used metrics and tools to assess a classification model are:

  A. Confusion Matrix
  B. Cost-sensitive accuracy
  C. Area under the ROC curve
  D. All of the above
  
  Eplanation
  The Correct Answer is D.
  
  

  Confusion matrix, Cost-sensitive accuracy and Area under the ROC curve

• Which of the following is a widely used and effective machine learning algorithm based on the idea of bagging?

  A. Decision Tree
  B. Regresion
  C. Classification
  D. Random Forest
  
  Eplanation
  The Correct Answer is D.
  
  

  The Radom Forest algorithm builds an ensemble of Decision Trees, mostly trained with the bagging method.

• Which of the following is a disadvantage of decision trees?

  A. Factor analysis
  B. Decision trees are robust to outliers
  C. Decision trees are prone to the be overfit
  D. None of the Above
  
  Eplanation
  The Correct Answer is C.
  
  

  Allowing a decision tree to split to a granular degree makes decision trees prone to learning every point extremely well to the point of perfect classification that is overfitting.

• Which of the following is a reasonable way to select the number of principal components "k"?

  A. Choose k to be the smallest value so that at least 99% of the varinace is retained.
  B. Choose k to be 99% of m (k = 0.99*m, rounded to the nearest integer).
  C. Choose k to be the largest value so that 99% of the variance is retained.
  D. Use the elbow method
  
  Eplanation
  The Correct Answer is A.
  
  

  This will maintain the structure of the data and also reduce its dimension.

• Which of the folllowing is an example of feature extraction?

  A. Constructing bag of words vector from an email
  B. Applying PCA projects to a large high-dimensional data
  C. Removing stopwords in a sentence
  D. All of the above
  
  Eplanation
  The Correct Answer is D.
  
  

  Constructing bag of words vector from an email, Applying PCA projects to a large high-dimensional data, and Removing stopwords in a sentence.

• Which of the following statements about regularization is not correct?

  A. Using too large a value of lambda can cause your hypothesis to underfit the data.
  B. Using too large a value of lambda can cause your hypothesis to overfit the data.
  C. Using a very large value of lambda cannot hurt the performance of your hypothesis.
  D. None of the Above
  
  Eplanation
  The Correct Answer is D.
  
  

  None of the above

• How can you prevent a clustering algorithm from getting stuck in bad local optima?

  A. Set the same seed value for each run
  B. Use multiple random initializations
  C. Both A and B
  D. None of the Above
  
  Eplanation
  The Correct Answer is B.
  
  

  Use multiple random initializations