What are the three types of machine learning? Give an example of each.
What are the three types of machine learning? Give an example of each.
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14-Apr-2025
Updated on 16-Apr-2025
Khushi Singh
16-Apr-2025Machine learning includes three main types, namely supervised learning, unsupervised learning, and reinforcement learning, that vary in characteristics according to the data and problem type.
Supervised Learning stands as the most common ML type because it requires training the model with labeled datasets. All learning examples consist of a given input along with its established correct output. Through pattern identification the model gains ability to produce forecasts or breakdowns between inputs and accurate outputs. Supervised learning adopts spam email detection as one of its prime examples through the training of systems with pre-labeled "spam" and "not spam" email classes. Through exposure to labeled examples the system will develop its ability to evaluate unknown messaging content according to its acquired patterns.
The process of Unsupervised Learning deals with unlabeled datasets. The purpose of this method is to enable the model to uncover concealed patterns inside the dataset. Data exploratory analysis along with understanding big datasets becomes simpler through this technique. The effects of customer segmentation serve as a typical business scenario in marketing operations. Companies apply purchasing behavior and demographic classification methods together with browsing pattern analysis to develop targeted marketing approaches for specific customer segments, even without preassigned categories.
An agent under Reinforcement Learning makes decisions through environmental interaction which results in reward or penalty feedback signals. The system gets feedback through reward-based or penalty-based feedback that it uses to optimize the cumulative reward accumulation during its operations. The trial-and-error learning method serves as a standard practice for dynamic and uncertain operational spaces. The most public demonstration of AI learning includes programs that play either chess or Go or video games. The agents enhance their strategic approach through an endless process of discovering more effective actions for winning or losing.