What is Machine Learning? (en)
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Machine Learning is a branch of computer science that focuses on developing algorithms and techniques to create computer systems capable of learning from data. In machine learning, computers are trained to recognize patterns and rules within data, enabling them to make intelligent and accurate predictions or decisions based on that data.
The learning process in machine learning can be carried out using three main methods: supervised learning, unsupervised learning, and reinforcement learning.
- Supervised learning involves using labeled or annotated data to train an algorithm so that the computer can recognize patterns or relationships between data features and labels. Examples of supervised learning applications include image classification, stock price prediction, and spam email classification.
- Unsupervised learning, on the other hand, involves using unlabeled data to identify hidden patterns or structures within the data. Examples of unsupervised learning applications include data clustering and dimensionality reduction.
- Reinforcement learning involves a computer system learning through experience by taking actions and receiving feedback on whether the actions are correct or incorrect. The goal is to find the optimal decision or action that maximizes overall benefit.
Machine learning has a wide range of applications, including facial recognition, image analysis, speech recognition, forecasting, anomaly detection, and many more.