Neural Networks Interview Questions – Set 1

0

This page represents practice test consisting of objective questions on neural networks. This test can prove to be useful for interviews as well. These questions can prove to be useful for machine learning interns / freshers / beginners.

These questions are related with some of the following topics:

  • Introduction to neural networks
  • Perceptron / Sigmoid neuron
  • Types of neural networks
  • Cost function for neural networks

Practice Test on Neural Networks

A perceptron can take _______ binary inputs and produces ________ binary outputs?

Which of the following type of neurons can take any kind of inputs and not just binary inputs?

Which of the following is true for a perceptron?

In case of perceptrons, which of the following needs to be changed in order to classify inputs in different classes?

Which of the following type of neurons can output any real number between 0 and 1 and not just binary outputs?

Multilayer networks are also called as ________

Neural networks in which output from one layer is fed as input to another layer are called as ________

Neural networks in which information is fed both backward and forward are called as ________

The goal in training a neural network is to find weights and biases which ____________ cost function?

Neural network with two or more hidden layers can be called as __________

Which of the following techniques is/are used for training deep neural networks?

Ajitesh Kumar

Ajitesh Kumar

Ajitesh has been recently working in the area of AI and machine learning. Currently, his research area includes Safe & Quality AI. In addition, he is also passionate about various different technologies including programming languages such as Java/JEE, Javascript and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc.

He has also authored the book, Building Web Apps with Spring 5 and Angular.
Ajitesh Kumar

Leave A Reply

Time limit is exhausted. Please reload the CAPTCHA.