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Basics of Deep Learning

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Basics of Deep Learning
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18 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are Transformers known for?

They are primarily used for image processing tasks.

They are state-of-the-art for NLP, vision, etc., and use self-attention mechanisms.

They are mainly used for traditional programming tasks.

They are known for their ability to perform arithmetic calculations.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are Convolutional Neural Networks (CNNs) specialized for?

They are specialized for images.

They are specialized for text processing.

They are specialized for audio recognition.

They are specialized for time series analysis.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does a neural network process input data?

Input data is fed into a neural network, where each neuron computes a weighted sum of its inputs, applies a non-linear activation function, and passes it on.

Input data is directly outputted without any processing by the neural network.

Input data is converted into binary format and stored in memory without any computation.

Input data is processed by a single neuron that outputs the final result.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Name some tools and libraries for deep learning.

Scikit-learn

TensorFlow

Pandas

NumPy

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the key idea of Deep Learning?

Learn features automatically from raw data, instead of hand-crafting them.

Manually design features for data analysis.

Use traditional machine learning algorithms exclusively.

Focus on shallow neural networks for data processing.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the role of activation functions in a neural network?

They add non-linearity to the model.

They increase the number of layers in the network.

They reduce the training time of the model.

They improve the accuracy of the model without any data preprocessing.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What type of data are Recurrent Neural Networks (RNNs) used for?

Image data like photographs

Sequence data like text or time series

Static data like spreadsheets

Graph data like social networks

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