Training step
A training step is an iteration in which a model is updated during training using data and an optimization objective.
Deep Learning with R, Third Edition
A training step is one iteration that evaluates a model on a batch, computes its loss and gradients, and updates its parameters.
- How it is used
- Updates model weights for one batch and serves as the repeated unit of an epoch.
- How deep it goes
- Works through prediction, loss, gradient, and update code, then extends the procedure to backend-specific custom steps and metric handling.
- Examples
- Uses MNIST batches and a two-dimensional linear classifier, with TensorFlow, PyTorch, and JAX implementations.
- What you can do after
- Build it from scratch for a batch, or apply it through a custom Keras train_step() while retaining fit().
Read how Deep Learning with R, Third Edition explains training step →
Deep Learning with Python, Third Edition
A single update of a model on one batch, consisting of prediction, loss computation, gradient computation, and weight adjustment.
- How it is used
- Defines the per-batch weight update repeated by epochs and customizable within Keras fit().
- How deep it goes
- Works through predictions, loss, automatic gradients, and updates, then implements backend-specific steps; defers manual backpropagation derivatives.
- Examples
- Uses handwritten-digit batches, a JAX linear classifier, and custom Keras train_step() implementations.
- What you can do after
- Build it from scratch as a backend-specific per-batch update, or apply it via a custom Keras train_step() inside fit().
Read how Deep Learning with Python, Third Edition explains training step →
Related concepts
- fit methodused by · A fit method is an operation that learns or estimates model parameters, structure, or transformation statistics from supplied data.
- Keras modelpart of · A Keras model is a trainable object representing a neural-network computation and providing interfaces for training, evaluation, prediction, and saving.
- epochcontrasts with · In machine learning, an epoch is one complete pass through the training data during model training or optimization.
- batch sizeconfigured by · Batch size is the number of items grouped together for processing or computation as a single batch.
- Time-LLMconfigured by · Time-LLM is a language-model-based framework that adapts existing large language models for time-series forecasting.
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