Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform specific tasks without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence.
There are different types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning.
Supervised Learning
In supervised learning, the algorithm is trained on labeled data, meaning it learns to map input data to the correct output.
Unsupervised Learning
Unsupervised learning involves training the algorithm on unlabeled data, allowing the model to learn patterns and relationships on its own.
Reinforcement Learning
Reinforcement learning is a type of machine learning where an agent learns to make decisions by interacting with its environment and receiving rewards or penalties.
Machine learning has various applications, including natural language processing, computer vision, healthcare, finance, and more.
Machine learning is a powerful tool with a wide range of applications, and understanding its fundamentals can help in creating innovative solutions and advancing technology.