Data mining and machine learning. Both of these fields are closely related and involve extracting insights and patterns from large datasets.

Data mining involves the process of discovering patterns, correlations, and information from a large amount of data. It often includes techniques such as clustering, classification, association rule mining, and anomaly detection. Data mining is used in various industries for tasks like customer segmentation, market analysis, and fraud detection.

Machine learning, on the other hand, is a subset of artificial intelligence that focuses on developing algorithms and models that enable computers to learn from data and make predictions or decisions without being explicitly programmed. Machine learning techniques include supervised learning, unsupervised learning, and reinforcement learning. It finds applications in areas like image recognition, natural language processing, and recommendation systems.