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Machine Learning (ML)

Knowledge Base / Glossary: "Machine learning (ML) is a type of Artificial intelligence that involves training algorithms to learn from data in order to make predictions or take actions without being explicitly programmed. The algorithms used in machine learning are designed..."

Machine learning (ML) is a type of Artificial intelligence that involves training algorithms to learn from data in order to make predictions or take actions without being explicitly programmed. The algorithms used in machine learning are designed to improve their performance over time as they are exposed to more data and feedback, allowing them to adapt and improve their predictions and actions.

One of the key uses of Machine Learning is to make predictions or decisions based on data. For example, a Machine Learning algorithm might be trained on a large dataset of customer data in order to predict which customers are likely to churn, or to recommend products to customers based on their past purchases and browsing history. By using machine learning, businesses can make more accurate and personalized predictions and recommendations, which can help them to improve customer engagement and satisfaction.

Another use of Machine Learning is to automate tasks and processes. For example, a Machine Learning algorithm might be trained on a dataset of images in order to automatically recognize objects in the images, or to classify the images into different categories. By using machine learning, businesses can automate tasks that are time-consuming or tedious for humans to perform, allowing them to improve efficiency and productivity.

Overall, Machine Learning is a powerful tool that allows businesses to make more accurate and personalized predictions and recommendations, and to automate tasks and processes. By training algorithms on large datasets, businesses can use Machine Learning to improve their operations and deliver better products and services to their customers.