NYU-MLC

What is true about Machine Learning?

• Machine Learning (ML) is a field of computer science

• ML is a type of artificial intelligence that extract patterns out of raw data by using an algorithm or method

• The main focus of ML is to allow computer systems to learn from experience without being explicitly programmed or human intervention

• All of the above

Which of the following are ML methods?

• Based on human supervision

• Supervised Learning

• Semi-reinforcement Learning

• All of the above

How do you handle missing or corrupted data in a dataset?

• Drop missing rows or columns

• Replace missing values with mean/median/mode

• Assign a unique category to missing values

• All of the above

Which of the following is NOT supervised learning?

• Linear Regression

• Decision Tree

• PCA

• Naive Bayesian

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

• Training condition used

• Representation scheme used

• Type of feedback used

• Data structure used

Which of the following is not a regularization technique?

• L1 Score

• L2 Score

• R2 Score

• Dropout

 In Machine Learning project modeling is an iterative process but deployment is not.

• True

• False

Let’s say you want to use Transfer Learning from task A to task B. Which of the following would support the use of transfer learning.

• Task A and Task B have same input task

• You have lot more data of Task A than Task B

• Low level features from Task A could be helpful in Task B

• All the above

Which statistical model and supervised machine learning algorithm uses independent variables to predict the value of a dependent variables?

•  Linear regression

• Logistic regression

Which term describes the ability of a computer program to understand human language in both written and spoken form?

• Multi-proccessing

• Natural language processing