Metadata-Version: 2.1
Name: pylearn-ml
Version: 1.2.0
Home-page: https://github.com/JanSkn/machine-learning-library
Author: Jan Skowron
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: dill
Requires-Dist: matplotlib
Requires-Dist: pytest
Requires-Dist: sphinx
Requires-Dist: sphinx-theme-pd

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<!-- PROJECT LOGO -->
<br />
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  <a href="https://github.com/janskn/machine-learning-library">
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  <h3 align="center">PyLearn</h3>

  <p align="center">
    A simple library for machine learning topics.
    <br />
    <a href="https://pylearn-ml.readthedocs.io/en/latest/"><strong>Explore the docs »</strong></a>
    <br />
    <br />
    <a href="https://github.com/janskn/machine-learning-library/issues">Report Bug</a>
    ·
    <a href="https://github.com/janskn/machine-learning-library/issues">Request Feature</a>
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  <br />

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</div>



<!-- ABOUT THE PROJECT -->
## About The Project

PyLearn implements machine learning features from scratch.
It supports basic features of supervised and unsupervised learning.
<br />
<br />
You can
- create neural networks with dense layers, different activation functions and loss functions,
- cluster your data without previously known classes,
- classify data
- evaluate models
- and more

<br />
    Read the <a href="https://pylearn-ml.readthedocs.io/en/latest/">Documentation</a> for more information.
    <br />
    <br />

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## Installation

Install PyLearn using `pip`:
```sh
pip install pylearn-ml
````

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### Built With

The source code was built with Python, mainly using NumPy and Pandas.

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### Requirements

Requirements can be found under `docs/requirements.txt`.

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<!-- USAGE EXAMPLES -->
## Usage

Import the library:
```python
import pylearn as pl
````

Most models have a _fit_ and a _predict_ function.

Just create a model, train it and use it for predictions.

```python
model = pl.Model()

model.fit(x_train, y_train)
...
model.predict(y_test)
```

For details of usage, have a look at the `examples` folder.
<br />
Or read the <a href="https://pylearn-ml.readthedocs.io/en/latest/">Documentation</a>



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<!-- CONTRIBUTING -->
## Contributing

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".

1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request

**Please follow the [Contributing](.github/CONTRIBUTING.md) guidelines.**

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<!-- LICENSE -->
## License

Distributed under the MIT License. See `LICENSE` for more information.

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