Interns – Machine Learning Interview Questions & Answers: Set 1

This page lists down first set of machine learning / data science interview questions and answers for interns / freshers / beginners. If you are an intern or a fresher or a beginner in machine learning field, and, you are looking for some practice tests before appearing for your upcoming machine learning interview, these practice tests would prove to be very useful and handy.

Machine Learning topics covered in Test

In this set, some of the following topics have been covered:

Machine learning fundamentals (Supervised and unsupervised learning algorithms)
Different types of machine learning problems and related algorithms with examples
Concepts related with regression, classification and clustering

Practice Test (Questions and Answers)

How much marks a strudent can get in a competitive exam based on hours of study and other related factors can be solved using _________ regression model

Multilinear regression

Logistic regression

Correct! Wrong!

The requirement related with grouping news in different classes can be solved using which of the following?

Regression

Classification

Clustering

None of the above

Correct! Wrong!

Whether a person is suffering from a disease can be solved using which of the following?

Multilinear regression

Logistic regression

Correct! Wrong!

Linear regression analysis helps in studying __________ relationship between variables.

Deterministic

Statistical

Correct! Wrong!

Classification problem falls under which category?

Supervised learning

Unsupervised learning

Reinforcement learning

Correct! Wrong!

Logistic regression is used to predict _________ valued output?

Continuous

Discrete

Correct! Wrong!

Logistic regression algorithm can be termed as which of the following?

Supervised learning algorithm

Unsupervised learning algorithm

Correct! Wrong!

Regression analysis helps in doing which of the following?

Causal analysis

Effects in forecasting

Forecasting trends

All of the above

Correct! Wrong!

In _ regression, there is dependent variable and independent variable(s)

Simple linear, one, multiple

Multiple, multiple, one

Simple linear, one, one

Multiple, one, multiple

Correct! Wrong!

Linear or multilinear regression helps in predicting _______

Continuous valued output

Discrete valued output

Correct! Wrong!

In _ regression, there is dependent variable and independent variable(s)

Simple linear, multiple, one

Simple linear, one, multiple

Multiple, one, multiple

Multiple, multiple, multiple

Correct! Wrong!

Best fit line for linear regression is also termed as _______

Maximum squares regression line

Least squares regression line

Correct! Wrong!

regression can be termed as a special case of _ regression when the outcome variable is categorical

Logistic, Linear

Linear, Logistic

Correct! Wrong!

Which of the following can be used to solve both classification and regression (numeric) problem?

Multilinear regression

Logistic regression

Support vector machine

Simple linear regression

Correct! Wrong!

K-Means algorithm belongs to which class of problems?

Numeric regression

Classification

Clustering

None of the above

Correct! Wrong!

Which of the following is an ensemble technique?

Bagging

Boosting

Both of the above

None of the above

Correct! Wrong!

Which of the following can be used for both classification and regression?

K-nearest neighbours

Support vector machine

Both of the above

None of the above

Correct! Wrong!

Machine Learning Interview Questions (Freshers) - Set 1

You did extremely well!!

You did reasonably well!!

Better luck next time!!

Useful links for Brush-up

Following is the list of some good links for brushing up AI / machine learning / Data Science concepts:

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. For latest updates and blogs, follow us on Twitter. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking. Check out my other blog, Revive-n-Thrive.com

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Interns – Machine Learning Interview Questions & Answers: Set 1

Machine Learning topics covered in Test

Practice Test (Questions and Answers)

How much marks a strudent can get in a competitive exam based on hours of study and other related factors can be solved using _________ regression model

The requirement related with grouping news in different classes can be solved using which of the following?

Whether a person is suffering from a disease can be solved using which of the following?

Linear regression analysis helps in studying __________ relationship between variables.

Classification problem falls under which category?

Logistic regression is used to predict _________ valued output?

Logistic regression algorithm can be termed as which of the following?

Regression analysis helps in doing which of the following?

In _________ regression, there is ________ dependent variable and ________ independent variable(s)

Linear or multilinear regression helps in predicting _______

In _________ regression, there is ________ dependent variable and ________ independent variable(s)

Best fit line for linear regression is also termed as _______

________ regression can be termed as a special case of _________ regression when the outcome variable is categorical

Which of the following can be used to solve both classification and regression (numeric) problem?

K-Means algorithm belongs to which class of problems?

Which of the following is an ensemble technique?

Which of the following can be used for both classification and regression?

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In _ regression, there is dependent variable and independent variable(s)

In _ regression, there is dependent variable and independent variable(s)

regression can be termed as a special case of _ regression when the outcome variable is categorical