Intermediate · Systems
Input generator
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A component that processes raw data into the tensor format suitable for input into a neural network during training or inference.
Technical Definition
A component that processes raw data into the tensor format suitable for input into a neural network during training or inference.
How it works
An input generator is a utility within a machine learning pipeline responsible for data loading and preprocessing. It takes raw data, transforms it into tensors, and then yields batches of these tensors that can be efficiently fed into a neural network. This component is essential for managing the flow of data during training, evaluation, and inference phases.
Related Concepts
- Neural Network — A computing system inspired by biological neural networks that learns patterns from data through interconnected layers of nodes.
- Training — The process of adjusting a model's parameters so it learns patterns from labeled or unlabeled data.
- Data Preprocessing — Transforming raw data into a format suitable for model training.
- Tensor — A multidimensional array used to represent data in many dimensions, fundamental to deep learning.