modeling techniques in predictive analytics with
tionships Variants include Deep Learning architectures (CNNs, RNNs, Transformers) Applications: Image and speech recognition Natural language processing Time series forecasting Strengths: Capture complex patterns Highly flexible Limitations: Require large datasets and