How AI Models Are Trained
Different training methods for AI models
During training, there are different ways to teach an AI model:
1. Learning from Examples
We show the model many examples. This is called training data.
There are two types:
1.1. Supervised Learning The training data includes the correct result. Example: Images labeled as "cat" or "dog".
1.2. Unsupervised Learning The training data does not have labels or results. The model has to detect patterns on its own. Example: Clustering similar items together or reducing data dimensions.
2. Reinforcement Learning
The model learns through feedback. We reward the model when it does something right and punish it when it does something wrong.
3. Other Methods
There are a few more advanced approaches.
Learning from examples (method 1) is the most common.
To improve, the model needs to measure its performance.
Sometimes you can start with a pretrained model and improve it with your specific data.