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    "info": {
        "author": "Lorenzo Palloni",
        "author_email": "palloni.lorenzo@gmail.com",
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        "description": "\n# QuickNN\n\nThe *quicknn* is a Tensorflow-based package that aims to simplify the application of the feedforward neural networks in classification and regression problems.\nThe main features of the *quicknn* package are:\n\n* internally management of the categorical variables with one-hot-encoding(OHE) method batch-wise, just you have to feed it with pandas object;\n* internally management of the validation of the data while training;\n* possibility to stop the training phase, change some parameters and then resume the training from where it had remained;\n* allows easy visualization of the learning curves using [Tensorboard](https://www.tensorflow.org/guide/summaries_and_tensorboard);\n\n## Example\n\n```python\nfrom quicknn import QuickNN\nfrom sklearn.datasets import load_boston\nfrom sklearn.model_selection import train_test_split\n\nX, y = load_boston(return_X_y=True)\nX_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.25)\n\nqnn = QuickNN(list_neurons=[100, 200, 1])\nqnn.fit(X_train, y_train, n_epochs=10) ## In IPython session you can stop-change-resume the training.\nqnn.fit(X_train, y_train, n_epochs=20) ## Just increasing the n_epochs.\nqnn.fit(X_train, y_train, n_epochs=30,\n        learning_rate=0.01) ## You can change e.g., the learning_rate param while training\ny_pred = qnn.predict(X_val)\n\n```\n\n## Installing\nThe dependencies are showed in [requirements.txt](requirements.txt), which can be installed with the command:\n```bash\n$ pip install -r requirements.txt\n```\nThen the library can easily downloaded through pip:\n```bash\n$ pip install quicknn\n```\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details.\n\n## References\n* [IPython](https://ipython.org/)\n* [Tensor](https://www.tensorflow.org/)\n* [pandas](https://pandas.pydata.org/)\n* [scikit-learn](http://scikit-learn.org/stable/)\n* [path.py](https://github.com/jaraco/path.py)\n\n\n",
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