Supervised Learning with real-world examples
1 min readMar 7, 2023
Supervised learning is a type of machine learning where a model learns from labeled data to make predictions. Some examples are:
- Image and object recognition: A model is trained with images that have labels such as “cat”, “dog”, “car”, etc. and then it can recognize new images that belong to those categories.
- Predictive analytics: A model is trained with historical data that have features such as age, income, location, etc. and a target variable such as customer churn, sales, revenue, etc. and then it can predict future outcomes based on new data.
- Customer sentiment analysis: A model is trained with text data that have labels such as “positive”, “negative”, “neutral”, etc. and then it can analyze new text data such as reviews, tweets, comments, etc. and assign them a sentiment score.
- Spam detection: A model is trained with email data that have labels such as “spam” or “not spam” and then it can filter out unwanted emails based on their content.
