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🧠 Quiz

Quiz: Inside a Neural Network: Neurons, Weights, and Biases Explained

Question 1 of 9

Why are artificial neural networks named after the brain?

They copy how the brain learns

They are made of biological neurons

They look like brain cells under a microscope

They were invented by neuroscientists

Question 2 of 9

What are the three types of layers in an artificial neural network structure?

Input layer, hidden layers, and output layer

Data layer, processing layer, and result layer

Receiving layer, computing layer, and answer layer

First layer, middle layers, and final layer

Question 3 of 9

What range of values does a neuron's output fall between?

0 and 1

-1 and 1

0 and 100

1 and 10

Question 4 of 9

If you're identifying apples from photos with 28×28 pixels, how many neurons would be in the input layer?

784 neurons

56 neurons

28 neurons

1568 neurons

Question 5 of 9

How many hidden layers would typically be needed for recognizing a fruit? (This question is very specific to the post https://infolia.ai/archive/35)

3-4 layers

1-2 layers

More layers (unspecified amount)

5-6 layers

Question 6 of 9

What does a high weight value indicate in neural network connections?

That input is important (loud signal)

That input should be ignored completely

That input is not important (quiet signal)

That input needs to be processed separately

Question 7 of 9

In the house price prediction example, what does the bias of 50,000 represent (This question is very specific to the post https://infolia.ai/archive/35)?

Base price even for size 0, because land costs money

The maximum price a house can have

The average price of all houses

The price per square foot

Question 8 of 9

Using the real example with Input: [0.5, 0.3, 0.8], Weights: [2, 3, 1], and Bias: 0.5, what is the calculated output before the activation function?

3.2

0.96

2.7

3.7

Question 9 of 9

How do weights start initially before training begins?

As random numbers

All set to zero

All set to one

Based on expert knowledge

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