What are the different types of Machine learning algorithms?
Answers
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Machine learning algorithms can be broadly categorised into three types: supervised learning, unsupervised learning, and reinforcement learning.
• Supervised learning is where the algorithm is trained on a set of labelled data, with the correct output already known. This allows the algorithm to learn how to predict the correct output when given new input data.
• Unsupervised learning, on the other hand, is where the algorithm is given a set of data without any labels or specific outcomes. The algorithm is then expected to identify patterns and relationships within the data on its own.
• Reinforcement learning involves the algorithm being trained to take certain actions in an environment to maximise a reward. This type of learning is often used in robotics or gaming applications.
Within these three categories, there are many different types of machine learning algorithms, including decision trees, neural networks, k-nearest neighbours, and principal component analysis. Each algorithm has its characteristics and can be applied in specific situations depending on the data and problem at hand.
