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 learningNone of the above
Correct
Question 6
What is a statistical model that uses Logistic function to model the conditional probability?
Ridge regressionStepwise RegressionLinear 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