Which machine learning algorithm is commonly used for solving classification and regression tasks, such as speech recognition?

Linear Regression
K-Nearest Neighbors (KNN)
Support Vector Machine (SVM)
Recurrent Neural Network (RNN)

The correct answer is D. Recurrent Neural Network (RNN).

A Recurrent Neural Network (RNN) is a type of artificial neural network that is commonly used for solving classification and regression tasks, such as speech recognition. RNNs are able to learn long-term dependencies between data points, which makes them well-suited for tasks that involve

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sequential data, such as speech recognition.

Linear Regression is a supervised machine learning algorithm that is used to predict continuous values. It is a simple algorithm that works by finding a linear relationship between the input features and the output label.

K-Nearest Neighbors (KNN) is a supervised machine learning algorithm that is used for classification and regression tasks. It works by finding the k nearest neighbors of a given data point and then using the labels of those neighbors to predict the label of the data point.

Support Vector Machine (SVM) is a supervised machine learning algorithm that is used for classification and regression tasks. It works by finding a hyperplane that separates the data points into two classes.

In conclusion, the correct answer is D. Recurrent Neural Network (RNN).