Deep learning vs. machine learning: Understanding the differences

Machine learning (ML) and deep learning (DL) are pivotal AI technologies transforming various industries by enabling data-driven decision-making. ML models, which learn from data without explicit programming, excel with structured data and simpler tasks, while DL models, inspired by the human brain, handle vast amounts of unstructured data and complex tasks using neural networks. The differentiation between them lies in their structure, complexity, and data handling capabilities, with DL offering superior performance for tasks like image and speech recognition. However, DL models require more computational resources and are less interpretable than ML models.