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Generate realistic test data in Python fast. No dataset required

Learn the NumPy trick for generating synthetic data that actually behaves like real data.
Yale Insights

How Innovations in Understanding Everyday Data Can Power More Effective Aid

For a project in Bangladesh, Prof. Mushfiq Mobarak and his team used machine-learning models applied to mobile phone records ...
InfoQ

Tracking and Controlling Data Flows at Scale in GenAI: Meta’s Privacy-Aware Infrastructure

Aware Infrastructure (PAI) to support generative AI development while enforcing privacy across complex data flows. Using ...
IEEE

Data-Driven Solutions for Human Trafficking: Detection and Impact Analysis Using Machine Learning

Abstract: Human trafficking is a serious problem that requires new ideas and data-driven approaches to identify and solve. In this study, we analyze large datasets to identify patterns and anomalies ...
IEEE

Energy-Efficient Autism Spectrum Disorder Data Collection Mechanism using Wireless Sensor Networks and Internet-of-Things

Abstract: A patient's cognitive health may be better assessed using smart monitoring and assisted living technologies. Social skills, repetitive habits, verbal and nonverbal communication, and ...