neuralnetworkdriven
Neuralnetworkdriven is a descriptor used in technology and academic writing to denote systems, processes, or decisions that are primarily guided by neural networks. It indicates that neural models learn from data to map inputs to outputs, often in end-to-end fashion, rather than relying on manually crafted rules or traditional algorithmic logic.
The term is used in varying spellings and styles, including neural-network-driven, neural network-driven, or simply neural-network
Common domains for neuralnetworkdriven approaches include computer vision, natural language processing, speech and audio processing, robotics,
Implementation typically involves data collection and preprocessing, model selection and training using supervised, unsupervised, or reinforcement
Advantages of neuralnetworkdriven systems include the ability to model complex, nonlinear relationships and to scale with