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Machine Learning is a subfield of Artificial Intelligence (AI) that focuses on enabling machines to learn and improve from experience without being explicitly programmed. It involves developing algorithms and statistical models that can analyze and identify patterns in large datasets, and use these patterns to make predictions or decisions about new data.

There are three main types of Machine Learning: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning involves training a model on a labeled dataset to make predictions on new data. Unsupervised learning involves training a model on an unlabeled dataset to identify patterns and structures in the data. Reinforcement learning involves training a model to make decisions in a dynamic environment by providing feedback in the form of rewards or penalties.

Machine Learning has numerous applications in various fields, such as image and speech recognition, natural language processing, predictive analytics, recommendation systems, and autonomous vehicles, to name a few.