This type of algorithm is mainly used

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In the fields of AI and machine learning, algorithms are designed to learn from data, discover patterns, make predictions, or execute decisions without explicit programming. Algorithms can be simple, like sorting a set of numbers, or complex, like identifying objects in images or understanding natural language text. In the field of AI, algorithms are used to deal with areas beyond human capabilities. For problems like ", there is no need to use algorithms. The concept of algorithm is very broad, and our discussion mainly focuses on algorithms in


machine learning. In machine learning, algorithms are usually divided into the Malaysia Phone Number Data following categories: [Supervised learning algorithm] Supervised learning algorithms learn models by using labeled training data (inputs and corresponding outputs). By establishing a mapping from input to output, the model is able to make predictions on new unlabeled data. Common supervised learning algorithms include linear regression, decision trees, support vector machines, etc. [Unsupervised learning algorithm] Unsupervised learning algorithms learn






structure and patterns from data without explicit labels.  for tasks such as clustering, dimensionality reduction, and association rule mining. For example, K-means clustering, principal component analysis (PCA) and association rule mining are common unsupervised learning algorithms. If you are still not clear about the basic concepts of unsupervised learning, I recommend my previous article " It's not too late to get started with "AI unsupervised learning" ( words of dry information) ". It is related to this