The Problem of Overfitting in Machine Learning

By Lena Qian Introduction Machine learning stands as a pivotal element in contemporary data science, fundamentally altering the landscape of predictive analytics and decision-making across various domains. Despite its widespread adoption, a significant impediment persists in the form of overfitting, wherein machine learning models have high accuracy with training data but fail when presented with […]

Boost AI Fairness and Explainability with Amazon SageMaker Clarify

From hiring decisions to loan approvals and even healthcare recommendations, machine learning (ML) impacts our lives daily. Fairness and explainability are crucial in this context. Fairness means data is balanced, and model predictions are fair across groups. Checking for fairness ensures that negative outcomes are fair across all groups, such as age or gender. Explainability […]