Basics of Machine Learning

The study of enabling machines to learn from data to make decision without the help of humans is known as __________

• Machine Learning

• Artificial Learning

• Algorithm analysis

• Data collection

__________ is type of machine learning which is learning from examples of labeld data set

• Unsupervised learning

• Supervised learning

• Features

• Artificial general intelligence

__________ is when machine try to group objects with similar features

• Classification

• Regression

• Clustering

• Decision tree

AI is subset of machine learning

• True

• False

Which analysis helps to take preventive measure learning from data

• Descriptive analysis

• Diagnostic analysis

• Predictive analysis

• Prescriptive analysis

In a ML system, a _________ is used to collect the data about temperature or sound

• Picture

• Light

• Sensor

• Pressure

Which of the following machine learning algorithm can be used for imputing missing values of both categorical and continuous variables

• K-NN

• Linear Regression

• Logistic Regression

• Random Forest

Skewness is used to detect _________

• Outliers

• Data boundary

• Empty cell

• Noise

In a negatively skewed distribution

• Mean > Mode > Median

• Mode > Median > Mean

• Mean > Median > Mode

• Mode < Median > Mean

Machine learning approaches can be traditionally categorized into ______ categories.

• 3

• 4

• 7

• 9