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AI & ML Quiz

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AI & ML Quiz

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Basics of AI/ML

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Sunmola Israel
Sunmola Israel
Nigeria

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AI & ML Quiz
 

AI & ML QuizOnline version

Basics of AI/ML

by Sunmola Israel
1

What does supervised learning primarily require to train a model?

2

Which algorithm is commonly used to minimize a loss function via gradient descent?

3

What is overfitting?

4

Which ML paradigm learns from interactively by receiving feedback from the environment?

5

What role do features play in ML models?

6

Which metric is commonly used to evaluate binary classifiers?

7

What is the purpose of cross-validation?

8

Which of the following is a type of neural network best for sequential data?

9

What is bias-variance tradeoff?

10

Which learning approach aims to learn representations from unlabeled data?

11

what does AI stands for?

12

What is Artificial intelligence

13

What Is Machine Learning

14

Which Of The Following Is An Example Of AI?

15

What is the main goal of machine learning

16

Which industry uses AI for medical diagnosis?

17

What is the type of data machine learning requires?

18

Which of these is a benefit of AI?

19

What is a chatbot?

20

Which of the following is a concern about AI?

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Supervised learning uses input-output pairs with labels to learn mappings.

Gradient descent optimizes parameters by following negative gradients of the loss.

Overfitting captures noise in training data, harming generalization.

In reinforcement learning, agents learn via rewards from actions.

Features are the input variables used by models to learn patterns.

Accuracy and ROC-AUC assess how well predictions match true labels.

Cross-validation tests generalization by partitioning data into folds.

RNNs handle sequences by maintaining hidden state across time steps.

High bias -> underfitting; high variance -> overfitting; balance needed.

Unsupervised learning discovers structure without labeled targets.

 
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