Description: Anomaly prediction is the process of identifying unusual or atypical patterns in data using machine learning techniques. This approach is based on the premise that most data follows normal behavior, and any significant deviation from this pattern may indicate a problem or an opportunity. In the context of machine learning, which aims to automate the process of creating models, anomaly prediction becomes a powerful tool for detecting irregularities without the need for intensive manual intervention. The main characteristics of this process include the ability to handle large volumes of data, the identification of complex patterns, and the adaptation to different types of data, from time series to tabular data. The relevance of anomaly prediction lies in its application across various industries, where it can help prevent fraud, improve service quality, and optimize operational processes. As organizations generate and collect more data, the need for effective tools to identify anomalies becomes increasingly critical, making this technique an essential component of modern data analysis.
