semvec/pypi-packages huggingface dataset:
mdoutline 0.0.1
📝
Requires Python: >=3.9

# mdoutline

## Example usage:
```python
from mdoutline import Markdown

markdown_text = """
# The Art of Machine Learning

Machine learning is a branch of artificial intelligence (AI) that enables systems to learn and improve from experience without being explicitly programmed.

## Introduction

In recent years, machine learning has become a critical tool in a variety of fields, from healthcare to finance. This document explores its fundamentals and applications.

### What is Machine Learning?

Machine learning involves algorithms that can learn from and make predictions on data. These algorithms operate by building a model from sample inputs.

#### Types of Machine Learning

There are three primary types of machine learning:

1. **Supervised Learning**
2. **Unsupervised Learning**
3. **Reinforcement Learning**

### Key Concepts

Several key concepts underpin machine learning:

- **Algorithms**: Step-by-step procedures for calculations.
- **Data**: Raw information used to train models.
- **Models**: Mathematical representations of data.

## Applications

Machine learning applications are vast and varied:

### Healthcare

In healthcare, machine learning is used for:

- Predicting disease outbreaks
- Personalizing treatment plans
- Enhancing medical imaging analysis

### Finance

In the finance sector, applications include:

- Fraud detection
- Algorithmic trading
- Risk management

#### Fraud Detection

Machine learning algorithms can identify unusual patterns in transaction data, helping to detect fraudulent activity.

## Conclusion

Machine learning is transforming numerous industries by enabling more accurate predictions, better decision-making, and efficient processes.

## References

For further reading, consider the following resources:

- [Introduction to Machine Learning](https://example.com)
- [Machine Learning Mastery](https://example.com)
- [Deep Learning Book](https://example.com)

## Appendix

### Appendix A: Glossary

- **Algorithm**: A process or set of rules to be followed in calculations or other problem-solving operations.
- **Data**: Facts and statistics collected together for reference or analysis.
- **Model**: A simplified representation of reality used to simulate and understand complex systems.

### Appendix B: Further Reading

- [Artificial Intelligence: A Modern Approach](https://example.com)
- [Pattern Recognition and Machine Learning](https://example.com)
"""

md = Markdown(markdown_text)
print(md.outline())
print(md.outline("Algorithmic trading"))
```