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One type of AI, machine learning, allows systems to learn from data without being explicitly programmed. The patterns in the data can be identified by machine learning algorithms and used to make correct predictions or decisions.

The two main types of machine learning are supervised learning and unsupervised learning. Supervised learning is when the machine learning algorithm is working with labeled data, meaning the data has been tagged with the correct answer. The machine learning algorithm also learns to predict the correct answer for new data.

Unsupervised learning means the machine learning algorithm is a set of unlabeled data. The machine learning algorithm also supports finding patterns in the data without being given any guidance.

Machine learning is important in a variety of applications.

• Fraud detection: Machine learning algorithms are used to identify fraudulent transactions by looking for patterns associated with fraud.
• Recommendation systems: Machine learning algorithms are also used to recommend products or services to users based on their past behavior.
• Medical diagnosis: Machine learning algorithms can be used for diagnosing diseases by analyzing medical data.
• Self-driving cars: Machine learning algorithms are also used in controlling self-driving cars by identifying objects and obstacles in the environment.

Source: Towardsdatascience, emeritus, geeksforgeeks