Neural Network Model (NNet) Inference Task

A Neural Network Model (NNet) Inference Task is a ML model inference task designed for a neural network model to make predictions or decisions based on new, unseen data.

• Context:
  • It can be solved by a Neural Network Inference System (that implements a neural network inference algorithm).
  • It can range from being a Shallow Neural Network Inference Task to being a Deep Neural Network Inference Task.
  • It involves processing input data through one or more layers of neurons, each designed to identify and extract patterns and features from the data.
  • It can support applications requiring unstructured data prediction]]s, such as autonomous driving, medical diagnosis, and voice recognition.
  • ...
• Example(s):
  • CNN Inference Tasks, such as: ...
  • DNN Inference Tasks, such as: ...
  • ...
• Counter-Example(s):
  • Neural Network Training Task.
  • Traditional machine learning inference tasks, such as Decision Tree Inference and Logistic Regression Inference.
• See: NNet Training, Model Optimization, Hardware Acceleration, Real-Time Inference.

---

---

---