Machine Learning Quiz

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Test your ML knowledge.

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Saravanan Nallathambi

India

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1	Saravanan Nallathambi January 8, 2026	% 20	02:06

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Machine Learning Quiz


Machine Learning QuizOnline version Test your ML knowledge. by Saravanan Nallathambi 1 What is the main goal of supervised learning? a Tune hyperparameters b Predict labels for new data c Cluster data without labels d Find data anomalies 2 Which measure estimates model error on unseen data? a Learning rate b Model complexity c Generalization error d Training error 3 Which technique helps prevent overfitting by limiting model complexity? a Data augmentation b Regularization c Early stopping only d Dropout only in neural nets 4 What does cross-validation primarily help with? a Increase training speed b Assess model performance reliably c Reduce dataset size d Tune hardware usage 5 Which algorithm is typically used for linear classification? a K-Means b Principal Component Analysis c Logistic Regression d DBSCAN 6 What is gradient descent used for? a Maximize accuracy b Minimize a loss function c Shuffle data d Compute data distribution 7 Which activation function is commonly used in neural networks? a Sigmoid b ReLU c Softmax only for outputs d Tanhish 8 Which model is often used for non-linear decision boundaries? a PCA b Linear Regression c K-Means d Decision Tree / Random Forest 9 What is feature scaling important for? a Reducing model capacity b Algorithms converge faster c Creating new features d Increasing data size 10 Which learning paradigm uses unlabeled data? a Unsupervised learning b Semi-supervised learning only c Supervised learning d Reinforcement learning

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Machine Learning Quiz

Quiz

About this activity

Created by

Download the paper version to play

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Machine Learning QuizOnline version

by Saravanan Nallathambi

What is the main goal of supervised learning?

Which measure estimates model error on unseen data?

Which technique helps prevent overfitting by limiting model complexity?

What does cross-validation primarily help with?

Which algorithm is typically used for linear classification?

What is gradient descent used for?

Which activation function is commonly used in neural networks?

Which model is often used for non-linear decision boundaries?

What is feature scaling important for?

Which learning paradigm uses unlabeled data?