Linear regression and logistic regression are algorithms utilized by:

Linear regression and logistic regression are indeed algorithms utilized by machine learning. Machine learning is a branch of artificial intelligence that focuses on the development of algorithms that can learn from and make predictions based on data.

Linear regression is used for predicting a continuous outcome variable based on one or more predictor variables, making it a fundamental statistical method for understanding relationships within numerical data. On the other hand, logistic regression is applied when the outcome is binary or categorical, allowing for predictions about the probability of certain outcomes. Both techniques are foundational in the field of statistics and play a crucial role in various machine learning applications, such as predictive analytics, risk assessment, and trend analysis.

The other options, while relevant in technology and data management contexts, do not pertain directly to the algorithms mentioned. Outsourced operations refer to the practice of delegating business processes to third parties and do not typically involve specific machine learning algorithms. Cloud computing, which involves delivering computing services over the internet, can facilitate the storage and processing of data but does not specifically relate to the algorithms used in machine learning. Thus, machine learning is the most appropriate context for discussing linear and logistic regression.