Machine learning is a subfield of artificial intelligence that focuses on developing algorithms and statistical models that enable computers to learn from and make predictions or decisions based on input data. Instead of explicitly programming a computer to perform a task, such as recognizing a face or translating text, machine learning algorithms use patterns in data to automatically learn how to perform these tasks.
There are several types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. Supervised learning algorithms are trained on labeled data, where the correct output is provided for each input example. Unsupervised learning algorithms, on the other hand, are trained on unlabeled data and attempt to find patterns or structure in the data without guidance. Reinforcement learning algorithms learn by trial and error, receiving feedback in the form of rewards or penalties for their actions.
Machine learning has many practical applications, such as image recognition, natural language processing, recommender systems, fraud detection, and predictive maintenance. It is a rapidly growing field, with new techniques and applications emerging all the time.