Inference
The process of using a trained model to make predictions on new, unseen data.
In-depth explanation
Once a model is trained, inference is the deployment phase where the model processes new inputs and produces outputs. Inference needs to be fast and efficient, especially in production systems. Techniques like model optimization, quantization, and specialized hardware (GPUs, TPUs) help speed up inference.
Examples
Related terms
More in AI Fundamentals
Artificial Intelligence (AI)
The simulation of human intelligence processes by computer systems, including learning, reasoning, and self-correction.
Machine Learning
A subset of AI where systems automatically learn and improve from experience without being explicitly programmed.
Deep Learning
A subset of machine learning using artificial neural networks with multiple layers to model complex patterns.
Algorithm
A set of step-by-step instructions or rules followed to solve a problem or perform a computation.
Model
A mathematical representation learned from data that can make predictions or decisions on new, unseen data.
Training
The process of teaching a machine learning model to make predictions by exposing it to data and adjusting its parameters.
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