Explore the fundamental concepts of Artificial Intelligence and Machine Learning, their differences, applications, and integration into software systems.
Explore comprehensive strategies and patterns for ensuring data privacy and compliance in AI systems, including techniques like anonymization, differential privacy, and federated learning, alongside practical implementations and ethical considerations.
Explore comprehensive strategies for monitoring and maintaining AI models post-deployment. Learn about key metrics, detecting model drift, setting up alerts, and automating retraining processes to ensure continued model performance.