Despite its benefits, machine learning also comes with challenges. High-quality data is essential for accurate results, and biased or incomplete data can lead to incorrect predictions.
Additionally, developing machine learning models requires technical expertise and computational resources. Ethical concerns, including data privacy and algorithmic bias, are also important considerations as machine learning continues to expand globally.
