Deep Learning 57 Flashcards Advanced 100% Free

Deep Learning::Convolutional Neural Networks

Created by Chat Robotics Community  ·  Updated 2025-07-19

Curriculum Overview

Topics & Key Concepts

Deep Learning Cnn

Sample Flashcard Questions & Answers

Showing 8 of 57 cards
Question #1 Active Recall

What is a Convolutional Neural Network (CNN)?

Answer & Explanation:
A CNN is a class of deep neural networks typically used for analyzing visual imagery. It leverages the spatial structure in images to achieve state-of-the-art performance in tasks such as image classification, object detection, and more.
Question #2 Active Recall

What is the primary building block of a CNN?

Answer & Explanation:
The primary building block of a CNN is the convolutional layer, which applies convolution operations over the input data to extract features.
Question #3 Active Recall

What does a convolution operation do?

Answer & Explanation:
A convolution operation involves sliding a filter or kernel over the input feature map to compute the dot product, producing an output called the feature map.
Question #4 Active Recall

What are pooling layers used for in CNNs?

Answer & Explanation:
Pooling layers reduce the spatial size of the feature maps to decrease the number of parameters and computations in the network, helping to control overfitting.
Question #5 Active Recall

What is the difference between max pooling and average pooling?

Answer & Explanation:
Max pooling takes the maximum value from each patch of the feature map, while average pooling calculates the average value.
Question #6 Active Recall

What are activation functions in CNNs?

Answer & Explanation:
Activation functions introduce non-linearity into the network. Common activation functions include ReLU (Rectified Linear Unit), sigmoid, and tanh.
Question #7 Active Recall

What is the purpose of a fully connected layer in a CNN?

Answer & Explanation:
Fully connected layers connect every neuron in the previous layer to every neuron they contain and are typically used at the end of the network for classification tasks.
Question #8 Active Recall

What is the role of the softmax function in CNNs?

Answer & Explanation:
The softmax function is used in the output layer of a CNN for multi-class classification problems, converting raw scores into probabilities.

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