## Eazyml Augmented Intelligence
  
A collection of APIs to discover patterns, generate insights, and uncover
rules in training datasets. Each discovered pattern is expressed as a set of
rules/conditions on feature variables, allowing users to analyze and apply
these insights to their data. Ideal for pattern recognition, interpretable AI,
and augmented intelligence workflows
### Features
- **Pattern Mining**: Discover meaningful rules in datasets.
- **Insight Generation**: Generate high-value insights with associated scores.
- **Application of Rules**: Apply discovered patterns to datasets for further analysis.
Ideal for use cases like interpretability, training data analysis, and building augmented intelligence solutions.
## Installation
### User installation
The easiest way to install augmented intelligence is using pip:
```bash
pip install -U eazyml-augi
```
### Dependencies
Eazyml Augmented Intelligence requires :
- werkzeug,
- unidecode,
- pandas,
- scikit-learn,
- nltk,
- pyyaml,
- requests
## Usage
Augmented Intelligence can be used by initalizing EazyML and then getting insights for given training data.
```python
from eazyml_augi import ez_init, ez_augi
# Replace 'your_license_key' with your actual EazyML license key
ez_init(license_key="your_license_key")
# Perform data insights for given training data using EazyML.
response = ez_augi(mode='classification',
outcome='target',
train_file_path='train.csv')
```
You can find more information in the [documentation](https://eazyml.readthedocs.io/en/latest/packages/eazyml_augi.html).
## Useful links and similar projects
- [Documentation](https://docs.eazyml.com)
- [Homepage](https://eazyml.com)
- If you have more questions or want to discuss a specific use case please book an appointment [here](https://eazyml.com/trust-in-ai)
- Here are some other EazyML's packages :
- [eazyml](https://pypi.org/project/eazyml/): Eazyml provides a suite of APIs for training, testing and optimizing machine learning models with built-in AutoML capabilities, hyperparameter tuning, and cross-validation.
- [eazyml-dq](https://pypi.org/project/eazyml-dq/): `eazyml-dq` provides APIs for comprehensive data quality assessment, including bias detection, outlier identification, and data drift analysis.
- [eazyml-cf](https://pypi.org/project/eazyml-cf/): `eazyml-cf` provides APIs for counterfactual explanations, prescriptive analytics, and actionable insights to optimize predictive outcomes.
- [eazyml-augi](https://pypi.org/project/eazyml-augi/): `eazyml-augi` provides APIs to uncover patterns, generate insights, and discover rules from training datasets.
- [eazyml-xai](https://pypi.org/project/eazyml-xai/): `eazyml-xai` provides APIs for explainable AI (XAI), offering human-readable explanations, feature importance, and predictive reasoning.
- [eazyml-xai-image](https://pypi.org/project/eazyml-xai-image/): eazyml-xai-image provides APIs for image explainable AI (XAI).
## License
This project is licensed under the [Proprietary License](https://github.com/EazyML/eazyml-docs/blob/master/LICENSE).
---
*Maintained by [EazyML](https://eazyml.com)*
*© 2025 EazyML. All rights reserved.*
Raw data
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