automated machine learning
The technique of teaching computers to learn from data is known as machine learning. A subset of artificial intelligence (AI) encompasses it. Automated machine learning (AutoML), as its name implies, is a method of fully automating the process of using machine learning to solve issues in the real world. Algorithms are used in this process to automatically choose and improve machine learning models. It may be used to automatically choose algorithms, prepare data, and adjust hyperparameters. By minimizing the need for human interaction, AutoML may be utilized to speed up the machine-learning process. The optimal algorithms and hyperparameters are automatically chosen, which can increase the precision of machine learning models.
A branch of artificial intelligence called automated machine learning is concerned with developing algorithms that can automatically develop and improve machine learning models. It may be used to improve a wide range of machine-learning models, including clustering, classification, and regression, among others. These algorithms are capable of choosing the optimal machine learning algorithm automatically for a certain dataset and job and can also automatically adjust the hyperparameters of the selected algorithm.
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