Which machine learning algorithm is commonly used for image classification tasks and is based on convolutional neural networks (CNNs)?
A. Decision Tree
B. Naive Bayes
C. K-Means Clustering
D. Convolutional Neural Network (CNN)
In machine learning, what is the term for the process of dividing a dataset into a training set and a testing set for model evaluation?
A. Data Sampling
B. Data Cleaning
C. Data Splitting
D. Data Transformation
What is the primary goal of gradient boosting algorithms in machine learning?
A. To maximize the margin between classes
B. To minimize prediction errors
C. To perform unsupervised learning
D. To visualize data relationships
Which machine learning algorithm is suitable for clustering data points into groups based on similarity?
A. Linear Regression
B. Support Vector Machine (SVM)
C. K-Means Clustering
D. Principal Component Analysis (PCA)
In machine learning, what is the term for the process of transforming categorical data into numerical format for modeling?
A. Data Aggregation
B. Data Encoding
C. Data Normalization
D. Data Imputation
Which machine learning algorithm is commonly used for natural language processing (NLP) tasks like sentiment analysis?
A. Linear Regression
B. Support Vector Machine (SVM)
C. Naive Bayes
D. Recurrent Neural Network (RNN)
What is the primary purpose of a k-nearest neighbors (KNN) algorithm in machine learning?
A. To build decision trees
B. To classify data points based on neighbors
C. To visualize data relationships
D. To fit linear regression models
Which machine learning algorithm is used for dimensionality reduction and is particularly useful in image compression?
A. Principal Component Analysis (PCA)
B. K-Means Clustering
C. Decision Tree
D. Naive Bayes
What is the primary goal of a neural network in machine learning?
A. To visualize data relationships
B. To minimize the error between predicted and actual values
C. To perform unsupervised learning
D. To simulate the human brain's function
Which machine learning algorithm is commonly used for anomaly detection, such as detecting fraudulent credit card transactions?
A. Random Forest
B. Decision Tree
C. Support Vector Machine (SVM)
D. Naive Bayes
Which machine learning algorithm is suitable for clustering data points into groups based on similarity?
A. Linear Regression
B. Support Vector Machine (SVM)
C. K-Means Clustering
D. Principal Component Analysis (PCA)
In machine learning, what is the term for the process of transforming categorical data into numerical format for modeling?
A. Data Aggregation
B. Data Encoding
C. Data Normalization
D. Data Imputation
Which machine learning algorithm is commonly used for image classification tasks and is based on convolutional neural networks (CNNs)?
A. Decision Tree
B. Naive Bayes
C. K-Means Clustering
D. Convolutional Neural Network (CNN)
In machine learning, what is the term for the process of dividing a dataset into a training set and a testing set for model evaluation?
A. Data Sampling
B. Data Cleaning
C. Data Splitting
D. Data Transformation
What is the primary goal of gradient boosting algorithms in machine learning?
A. To maximize the margin between classes
B. To minimize prediction errors
C. To perform unsupervised learning
D. To visualize data relationships
Which machine learning algorithm is commonly used for natural language processing (NLP) tasks like sentiment analysis?
A. Linear Regression
B. Support Vector Machine (SVM)
C. Naive Bayes
D. Recurrent Neural Network (RNN)
What is the primary purpose of a k-nearest neighbors (KNN) algorithm in machine learning?
A. To build decision trees
B. To classify data points based on neighbors
C. To visualize data relationships
D. To fit linear regression models
Which machine learning algorithm is used for dimensionality reduction and is particularly useful in image compression?
A. Principal Component Analysis (PCA)
B. K-Means Clustering
C. Decision Tree
D. Naive Bayes
What is the primary goal of a neural network in machine learning?
A. To visualize data relationships
B. To minimize the error between predicted and actual values
C. To perform unsupervised learning
D. To simulate the human brain's function
Which machine learning algorithm is commonly used for anomaly detection, such as detecting fraudulent credit card transactions?
A. Random Forest
B. Decision Tree
C. Support Vector Machine (SVM)
D. Naive Bayes
