AI Assessment Challenge

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Sobre esta actividad

A quick AI knowledge check.

Creada por

Dr. Pushp Kumar Baghel

India

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Froggy Jumps AI Assessment ChallengeVersión en línea A quick AI knowledge check. por Dr. Pushp Kumar Baghel 1 What is overfitting in AI? a It reduces training time b Model ignores noise in data c Model fits training data too closely 2 Which metric is best for binary class imbalance? a Accuracy b AUC-ROC c Mean squared error 3 Which statement best describes supervised learning? a Uses labeled data to learn mapping b Uses unlabeled data c Does not require data for training 4 What is cross-validation? a Data cleaning method b Technique to assess model on multiple folds c Algorithm optimization 5 What does ROC-AUC measure? a Trade-off between TPR and FPR b Model speed c Prediction interval 6 What is the bias-variance tradeoff? a Balancing error from under/overfitting b Irrelevant to performance c Only about model size 7 What is data leakage in ML? a Test data info contaminates training b Label noise c Using more data improves performance 8 What describes reinforcement learning best? a Unsupervised clustering b Trains with labeled data c Agent learns by interacting with environment 9 Which technique reduces overfitting by ensembling? a Ensemble methods b Single large model c Dimensionality reduction 10 What is generalization in ML? a Faster training time b Model works well on unseen data c Performance only on training data

Froggy Jumps

AI Assessment ChallengeVersión en línea

A quick AI knowledge check.

por Dr. Pushp Kumar Baghel

What is overfitting in AI?

It reduces training time

Model ignores noise in data

Model fits training data too closely

Which metric is best for binary class imbalance?

Accuracy

AUC-ROC

Mean squared error

Which statement best describes supervised learning?

Uses labeled data to learn mapping

Uses unlabeled data

Does not require data for training

What is cross-validation?

Data cleaning method

Technique to assess model on multiple folds

Algorithm optimization

What does ROC-AUC measure?

Trade-off between TPR and FPR

Model speed

Prediction interval

What is the bias-variance tradeoff?

Balancing error from under/overfitting

Irrelevant to performance

Only about model size

What is data leakage in ML?

Test data info contaminates training

Label noise

Using more data improves performance

What describes reinforcement learning best?

Unsupervised clustering

Trains with labeled data

Agent learns by interacting with environment

Which technique reduces overfitting by ensembling?

Ensemble methods

Single large model

Dimensionality reduction

What is generalization in ML?

Faster training time

Model works well on unseen data

Performance only on training data

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AI Assessment Challenge

Froggy Jumps

Sobre esta actividad

Creada por

Descarga la versión para jugar en papel

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Froggy Jumps

AI Assessment ChallengeVersión en línea

por Dr. Pushp Kumar Baghel

What is overfitting in AI?

Which metric is best for binary class imbalance?

Which statement best describes supervised learning?

What is cross-validation?

What does ROC-AUC measure?

What is the bias-variance tradeoff?

What is data leakage in ML?

What describes reinforcement learning best?

Which technique reduces overfitting by ensembling?

What is generalization in ML?

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