1. Regression models: Regression models are used to predict the relationship between a dependent variable and one or more independent variables. These models are used to understand how changes in the independent variables affect the dependent variable. 2. Classification models: Classification models are used to categorize data into different classes or groups based on various features or attributes. These models are commonly used in fields like machine learning and data mining for tasks such as spam detection, sentiment analysis, and image recognition. 3. Time series models: Time series models are used to analyze and forecast time-dependent data, such as stock prices, sales figures, or weather patterns. These models take into account the sequential nature of the data and attempt to identify trends, seasonality, and other patterns. 4. Clustering models: Clustering models are used to group similar objects or data points together based on their characteristics or attributes. These models aim to identify natural groupings within the data without any prior knowledge of the groups. 5. Neural network models: Neural network models are artificial intelligence models inspired by the structure and function of the human brain. These models consist of interconnected nodes (neurons) that process and learn from data to make predictions or classifications. Neural networks are commonly used in tasks such as image and speech recognition, natural language processing, and anomaly detection.