Machine Learning Flashcard

Front

Which of the following best differentiates supervised from unsupervised learning? Supervised learning uses labeled data; unsupervised learning uses unlabeled data., Supervised learning uses unlabeled data; unsupervised learning uses labeled data., Both methods use only labeled data., Both methods use only unlabeled data.

Back

Supervised learning uses labeled data; unsupervised learning uses unlabeled data.

Front

Which of the following activation functions is used in neural networks? ReLU, Sigmoid, Softmax, All of the above

Back

All of the above

Front

A higher learning rate always improves model accuracy.

Back

False

Front

What is the primary purpose of gradient descent in machine learning?

Back

To minimize the cost function by iteratively updating parameters.

Front

Which of the following best describes overfitting in a machine learning model? High performance on training data and poor performance on unseen data.

Back

High performance on training data and poor performance on unseen data.

Front

Which algorithm is primarily used for classification tasks among the following? K-Means Clustering, Principal Component Analysis, Linear Regression.

Back

Random Forest Classifier

Front

What distinguishes batch gradient descent from stochastic gradient descent?

Back

Batch uses the entire dataset per iteration, stochastic uses one sample per iteration.

Front

Which evaluation metric is best suited for imbalanced classification datasets? Options: Accuracy, Mean Squared Error, Precision-Recall, R-squared

Back

Precision-Recall

Front

What is the primary advantage of using Convolutional Neural Networks (CNNs) for image processing?

Back

Ability to capture spatial hierarchies in images, Reduced number of parameters due to shared weights, Inherent translation invariance.

Front

What is the main purpose of using dropout in neural networks?

Back

To prevent overfitting by randomly deactivating neurons during training.