2. Deep Learning and Variants_Session 2_20240120 - Neural Networks for Classification Quiz

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30 Questions

What is the purpose of using logistic regression with the MTcars dataset?

To estimate the probability of a car having manual transmission based on its engine power and weight

What is a limitation of a single perceptron model?

It cannot handle non-linear data effectively

What does the region below the line in the perceptron model signify?

Negative output values

How does a single perceptron handle non-linearity in data?

By converting non-linear data into linear form

What are neurons like sigmoid et al. used for in deep learning?

To represent activation functions in neural networks

Based on biological inspiration, what would intuition suggest when dealing with non-linear data using a single perceptron model?

Use multiple layers of neurons like the human brain does

What is a key characteristic of a one hidden layer network?

It can learn any function

In Artificial Neural Networks, what do hyper-parameters refer to?

Parameters like activation functions and network structure

What is the purpose of using the softmax activation function in the output layer of a neural network?

To convert raw scores into probabilities for multi-class classification

Which type of neural network is specifically designed for problems with non-linear relationships between inputs and outputs?

Feed Forward Neural Network

What is the primary role of the transformation matrix in neural networks?

It represents all the connections between neurons as a matrix

What distinguishes Multi Layer Perceptrons from traditional perceptrons?

MLPs have multiple hidden layers, while perceptrons have only one

Which function is often used for the activation of neurons in the output layer of a neural network for regression problems?

Linear

What does the term 'hyper-parameters' typically refer to in the context of Artificial Neural Networks?

Network structure and activation functions

In a neural network, which function is commonly used in the output layer for multi-class classification problems?

Softmax

What is the primary role of a transformation matrix in a neural network?

Changing representation space

Which of the following is NOT a hyper-parameter in an Artificial Neural Network?

Weights and bias initialization method

For what type of problem is the Sigmoid activation function particularly useful in a neural network?

Classification problems

What distinguishes Multi Layer Perceptrons from traditional perceptrons?

Non-linearity handling capability

In deep learning, what do parameters like 'Number of hidden layers' and 'Number of neurons' represent?

'Hyper-parameters'

What is a key characteristic of a Multi Layer Perceptron (MLP)?

Consists of multiple hidden layers

What type of activation function is often employed in the output layer for binary classification problems?

Sigmoid

What model is used to estimate the probability of a vehicle being fitted with a manual transmission using the MTcars dataset?

Perceptron

In logistic regression, what does a positive value output by a single perceptron represent?

Region above the line

Why is a single perceptron not suitable for handling non-linear data?

It can't create a boundary beyond linear regions

What is the limitation of a single perceptron when dealing with binary classification similar to the 'Will it work here?' example provided?

It cannot represent non-linear decision boundaries

Based on biological inspiration, what approach would intuition suggest when dealing with non-linear data using artificial neurons?

Combine multiple layers of neurons

What is the primary role of the sigmoid function in artificial neural networks?

Handle non-linear relationships

In the given logistic regression formula, what does the term 'hp' represent?

Horsepower of the engine

'Will it work here?' table demonstrates an issue faced by which type of model due to its linearity?

'Perceptron' model

Test your knowledge on using neural networks for classification tasks, specifically logistic regression, with the MTcars dataset. Estimate the probability of a vehicle having manual transmission based on engine power and weight.

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