9.6.1.Final Exam - sj50179/IBM-Data-Science-Professional-Certificate GitHub Wiki

Final Exam

Latest Submission Grade 100%

Question 1

Which of the followings are true about Machine Learning?

  • Machine Learning models help us in tasks such as object recognition, summarization, and recommendation.
  • Machine learning gives computers the ability to make decision by writing down rules and methods and being explicitly programmed.
  • Machine Learning models iteratively learn from data, and allow computers to find hidden insights.
  • Machine Learning was inspired by the learning process of human beings.

Correct

Question 2

Which of the followings are a Machine Learning technique?

  • Clustering
  • Associations
  • Regression/Estimation
  • Heuristics

Correct

Question 3

Which of the following is true for Multiple Linear Regression?

  • Multiple independent variables are used to predict a dependent variable.
  • The relationship between the independent variable x and the dependent variable y is modeled as an nth degree polynomial in x.
  • One independent variable is used to predict a dependent variable.
  • Observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or more independent variables.

Correct

Question 4

In which of the following is correct for Polynomial Regression?

  • It can fit a curved line to your data.
  • It can be transformed into a linear regression model using the Least Squares method.
  • It can use the same mechanism as Multiple Linear Regression to find the parameters.
  • All of the above.

Correct

Question 5

Predicting whether a customer responds to a particular advertising campaign or not is an example of what?

  • Regression
  • Classification problem
  • Machine learning
  • None of the above

Correct

Question 6

What is a statistical model that uses Logistic function to model the conditional probability?

  • Ridge regression
  • Stepwise Regression
  • Linear regression
  • Logistic regression

Correct

Question 7

Which of the following statements is true for k-means clustering?

  • The object of k-means is to form clusters in such a way that similar samples go into a cluster, and dissimilar samples fall into different clusters.
  • Is one of the simplest unsupervised learning algorithms that solve well known clustering problems.
  • k-means divides the data into non-overlapping clusters without any cluster-interval structure.
  • All of the above.

Correct

Question 8

What does DBCSAN stand for?

  • Density-based Spatial Cores of Applications with Noise.
  • Density-Based Spatial Clustering of Applications with Noise.
  • Data-Based Spatial Clustering of Applications with Noise.
  • Data-Based Sample Clustering of Applications with Noise.

Correct

Question 9

What is/are the advantage/s of Recommender Systems ?

  • Recommender Systems provide a better experience for the users by giving them a broader exposure to many different products they might be interested in.
  • Recommender Systems encourage users towards continual usage or purchase of their product
  • Recommender Systems benefit the service provider by increasing potential revenue and better security for its consumers.
  • All of the above.

Correct

Question 10

What is a content-based recommendation system?

  • Content-based recommendation system tries to recommend items to the users based on their profile built upon their preferences and taste.
  • Content-based recommendation system tries to recommend items based on similarity among items.
  • Content-based recommendation system tries to recommend items based on the similarity of users when buying, watching, or enjoying something.
  • All of above.

Correct