BE - Machine Learning

The Basic Process 
1. Data Input 

    Machine receives lots of examples (data)
    Examples: images, numbers, text, sounds
     

2. Pattern Recognition 

    Algorithms search for patterns, relationships, and trends
    "What makes an email spam?" or "What do cats look like?"
     

3. Model Creation 

    Build a mathematical "model" - like a formula or set of rules
    This model represents what the machine learned
     

4. Testing & Feedback 

    Test the model on new data
    Measure how accurate it is
    Adjust and improve the model