# ML Batch Processing

Learn how to use TorchFX for batch processing audio data in machine learning pipelines.

## Overview

This tutorial covers:
- Loading and preprocessing audio datasets
- Applying effects and filters in batch mode
- GPU acceleration for large-scale processing
- Integration with PyTorch DataLoaders

## Prerequisites

- Basic Python knowledge
- Familiarity with PyTorch
- Understanding of audio signal processing basics

## Tutorial Content

```{todo}
*Coming soon! This tutorial is currently under development.*
```

## What You'll Learn

- How to efficiently process large audio datasets
- Best practices for batch audio augmentation
- Memory management techniques for GPU processing
- Creating custom preprocessing pipelines

## Example Code

```python
import torch
from torchfx import Wave, FX
from torchfx.filter import LoButterworth

# Example code will be added here
```

## Next Steps

After completing this tutorial, you may want to explore:
- [Real-time Processing](real-time-processing.md)
- [Filters Design](filters-design.md)
- [Custom Effects](custom-effects.md)
