Machine Learning 편집하기 (부분)

==Challenges in Machine Learning==
Despite its benefits, machine learning faces several challenges:
*'''Data Quality and Quantity''': Models require large and high-quality datasets, which can be difficult to collect or prepare.
*'''Interpretability''': Complex models, especially deep learning, can be hard to interpret, which limits their use in regulated industries.
*'''Bias and Fairness''': Machine learning models can perpetuate biases in the data, leading to unfair or discriminatory outcomes.
*'''Computational Resources''': Machine learning, especially with large models, requires significant computational power.