Discover how Hybrid AI combines symbolic AI and machine learning to boost accuracy, efficiency, and flexibility in AI applications like NLP, computer vision, and robotics.
Explore probability density functions, their properties, and their applications in AI. Understand data distribution, uncertainty modeling, and statistical analysis.
Explore semi-supervised learning: an ML approach combining labeled and unlabeled data. Learn its benefits, challenges, and how it compares to other methods.
