The foundation of modern AI. Computers that improve from experience without explicit programming.
Discuss ML ApplicationsMachine Learning (ML) is the practice of teaching computers to make decisions and predictions by learning from data, rather than following explicitly programmed rules.
Instead of writing "if-then" rules for every scenario, we show the computer thousands of examples, and it discovers the patterns on its own. The more data it sees, the better it gets, just like human learning.
Learning from labeled examples. You show the computer thousands of emails marked 'spam' or 'not spam,' and it learns to classify new emails.
Finding hidden patterns in unlabeled data. The computer discovers natural groupings and relationships without being told what to look for.
Learning through trial and error with rewards. The computer tries different approaches and learns from the results, like training a dog.
Banks use supervised learning to predict loan default risk by learning from millions of historical loans.
Retailers use unsupervised learning to discover natural customer groups for targeted marketing.
Manufacturers use reinforcement learning to optimize stock levels and reduce waste.
Telecom companies use supervised learning to identify customers likely to cancel service.