In today's data-driven world, machine learning (ML) models rely on vast amounts of information to power insights, automation, and decision-making. However, as organizations increasingly leverage these models, they must also address the critical challenge of protecting personally identifiable information (PII). Regulatory frameworks like GDPR, CCPA, and HIPAA place stringent requirements on how data is collected, processed, and shared, making privacy-preserving techniques essential for responsible AI and ML development.

Artificial intelligence (AI) is designed to enable computers to mimic human behavior and mind. It is evident in any machine or system that exhibits human-like behaviors. In the simplest form of AI, computers can be taught to mimic human behavior using data from previous instances of the activity. This includes everything from distinguishing between a cat and a bird to performing complex tasks in an industrial environment. AI allows machines to evaluate large volumes of data quickly and efficiently. They can find solutions using supervised, non-supervised, or reinforced learning.

Explore the latest trends and best practices in cloud-based data engineering, from data warehouse to data lake migration to automation, cost optimization, and security.