Data Science & AI

Models are destructive when opaque, unregulated, and unfair, causing widespread damage.

Break down complex interview problems into manageable, logical steps.

Understanding the end-to-end flow from data acquisition to deployment is crucial for su...

Success in data science relies more on a structured workflow than on specific algorithm...

AI systems often fail to accurately recognize or represent marginalized groups due to b...

Algorithms reflect and amplify human biases embedded in their data and design.

Learn to write simple Python scripts that perform repetitive actions faster and more re...

AI intelligence levels do not dictate its final goals, meaning a superintelligence coul...

Assess model performance using appropriate metrics and cross-validation to ensure real-...

Data's meaning and application are shaped by specific historical contexts and human cho...