what is dataset in machine learning

In machine learning, a dataset is a collection of data that is used to train a model and make predictions. It is a collection of separate pieces of data that can be treated as a single unit by a computer for analytic and prediction purposes. Datasets can include various types of data such as images, texts, audio, videos, numerical data points, etc.. The performance of any machine learning or deep learning model depends on the quantity, quality, and relevancy of the dataset. There are different types of datasets used in machine learning, including image datasets, text datasets, audio datasets, video datasets, and numerical datasets. A dataset is usually first labeled or annotated to help the machine learning algorithm understand what the outcome needs to be. The dataset is then divided into two parts: the training dataset and the test dataset. The training dataset is used to train the model, while the test dataset is used to evaluate the performance of the model. It is important to choose the right dataset for a machine learning project, as it can be the determinant between the success and failure of the project.