What Challenges Exist in Implementing Machine Learning?
While ML holds great promise, several challenges must be addressed:
Data Quality: High-quality, well-annotated datasets are essential for training effective ML models. Interpretability: It can be difficult to interpret how complex ML models arrive at their conclusions. Regulatory Compliance: Ensuring that ML applications comply with regulatory standards is critical, especially in fields like pharmaceuticals and clinical research. Ethical Concerns: Issues related to data privacy and security must be carefully managed.
