What is the primary purpose of a dataset in machine learning?

The primary purpose of a dataset in machine learning is to provide data for training a model. In machine learning, models learn patterns and relationships from data to make predictions or decisions based on new, unseen data. The dataset serves as the foundation for this learning process, containing examples that the model analyzes to understand how different features correlate with outcomes.

Training a model involves processing this dataset to adjust the model's parameters so that it can effectively generalize from the training data to unseen data. A well-constructed dataset is crucial for the success of a machine learning project, as it determines the quality and accuracy of the model's predictions.

While other options mention aspects related to data, such as storing unstructured data or visualizing data, these activities are not the primary functions of a dataset in the context of machine learning. Conducting experiments on raw data may also be part of the overall data science process but does not encompass the primary role of datasets in training machine learning models.