Machine Learning and Deep Learning are both subfields of Artificial Intelligence (AI) but have distinct differences. The main difference between Machine Learning and Deep Learning is that Deep Learning uses Artificial Neural Networks (ANNs) to process unstructured data, such as texts, images, sounds, and videos, and transform them into numerical values, while Machine Learning does not necessarily use ANNs and can work with structured and semi-structured data.

Machine Learning is a subset of AI that encompasses techniques, including Deep Learning, that allow computers to improve their performance through experience. The learning process in Machine Learning is based on feeding data into an algorithm, and the computer learns from the patterns and relationships within the data.

Deep Learning, on the other hand, is a subset of Machine Learning that focuses on using ANNs to process and learn from unstructured data. Deep Learning is particularly useful for applications that involve computer vision, natural language processing, and speech recognition, among others. Deep Learning requires a large amount of data and computing power to train the neural networks.