Machine learning is a branch of artificial intelligence focused on developing algorithms that allow computers to learn from and make predictions or decisions based on data.
Key aspects of machine learning include:
Supervised Learning: This involves training a model on labeled data, where the algorithm learns to map the input data to the correct output. It is used for tasks like classification (e.g., spam detection) and regression (e.g., predicting house prices).
Unsupervised Learning: Here, the algorithm is trained on unlabeled data and learns to find patterns and structures in the data. Clustering (e.g., grouping customers by behavior) and dimensionality reduction (e.g., feature selection) are common tasks in unsupervised learning.
Reinforcement Learning: This involves training agents to make sequences of decisions. The agent learns by interacting with an environment and receiving feedback in the form of rewards or penalties. Applications include game playing (e.g., AlphaGo) and robotics.
Deep Learning: A subset of machine learning that uses neural networks with many layers (hence “deep”). Deep learning has achieved remarkable success in tasks such as image and speech recognition, natural language processing, and autonomous driving.
Machine learning services
Machine learning services refer to a range of offerings provided by companies and platforms that enable businesses and developers to leverage machine learning capabilities without needing to build and maintain their own infrastructure from scratch.
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