Machine learning is a branch of artificial intelligence that enables computers to learn from and make decisions based on data, without being explicitly programmed for every task. It uses algorithms to find patterns in data, allowing systems to improve their performance over time as they are fed more information. This technology powers applications like personalized recommendations, fraud detection, and voice recognition, by enabling systems to identify patterns, make predictions, and classify data.  

• Pattern recognition:

  The core function is to identify patterns in data to make predictions about new, unseen data. 

   

   
• Learning and improvement:

  Instead of being given explicit instructions for every situation, a machine learning model learns through experience, becoming more accurate as it processes more data. 

   

   
• Training and testing:

  A model is typically trained on one set of data, and then its accuracy is tested on a separate, unseen dataset to validate its performance. 

   

   

• Classification: Categorizing data, such as identifying objects in images or spam emails. 
   
• Prediction: Forecasting future events, like stock prices or customer behavior. 
   
• Automation: Automating tasks and making decisions, such as fraud detection or autonomous driving.