AI Fundamentals Exercises

Fill in the blanks to test your knowledge.

1

Name the process of training a model on labeled data

// Learning from labeled examples

// Called learning

2

Identify the metric used to measure model error during training

// The function we minimize during training

// Called the function

3

Name the algorithm used to update neural network weights

// Computes gradients layer by layer

// Called

4

Identify the layer type that extracts local features from images

// Used in CNNs for image feature extraction

// Called a layer

5

Name the technique to prevent overfitting by randomly zeroing neurons

// Randomly disables neurons during training

// Called

6

Name the optimizer that adapts learning rates per parameter

// Adaptive learning rate optimizer

optimizer = (lr=0.001)

7

Identify the type of ML where an agent learns from rewards

// Agent learns through trial and error with rewards

// Called learning

8

Name the common activation function that outputs between 0 and 1

// Maps any value to (0, 1)

// Called the function