What are the main challenges in training AI models?

What are the main challenges in training AI models?

Some key challenges include data quality, overfitting, computational resources, and algorithm selection.

How does data quality affect model performance?

Data quality directly impacts model accuracy; poor data can lead to biased or incorrect predictions.

What is overfitting and how can it be prevented?

Overfitting occurs when a model learns noise instead of the signal. It can be prevented using techniques like cross-validation and regularization.

Can you explain the role of computational resources in training?

Computational resources determine how quickly and effectively a model can be trained, impacting the complexity and size of the model.

What algorithms are commonly used in AI model training?

Common algorithms include linear regression, decision trees, neural networks, and support vector machines.