Unsupervised learning is a way for computers to learn without being given clear answers.
In this type of machine learning, the model looks at data that isn’t labeled or categorized. This means it has to figure things out on its own.
Unsupervised learning is especially helpful for understanding how consumers behave when they shop.
Clustering: This is when computers group people based on what they buy. For example, a store might find that some customers buy a lot of fancy items.
Anomaly Detection: This means spotting things that are out of the ordinary, like someone who spends way more than usual. This can help catch fraud or show that a shopper has unique tastes.
Recommendation Systems: By looking at what people do, unsupervised learning can suggest products that shoppers might like. This makes shopping more enjoyable for them.
In summary, unsupervised learning gives businesses useful information. It helps them create better plans to meet their customers’ needs.
Unsupervised learning is a way for computers to learn without being given clear answers.
In this type of machine learning, the model looks at data that isn’t labeled or categorized. This means it has to figure things out on its own.
Unsupervised learning is especially helpful for understanding how consumers behave when they shop.
Clustering: This is when computers group people based on what they buy. For example, a store might find that some customers buy a lot of fancy items.
Anomaly Detection: This means spotting things that are out of the ordinary, like someone who spends way more than usual. This can help catch fraud or show that a shopper has unique tastes.
Recommendation Systems: By looking at what people do, unsupervised learning can suggest products that shoppers might like. This makes shopping more enjoyable for them.
In summary, unsupervised learning gives businesses useful information. It helps them create better plans to meet their customers’ needs.