Metadata-Version: 2.1
Name: nn-for-dummies
Version: 0.0.42
Summary: a small classfication neural network framework
Home-page: UNKNOWN
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown

# NN Framework For Dummies

*A simple neural network framework that use similar interface to TensorFlow*

#colab link

	https://colab.research.google.com/drive/1uXPiYy5kjNvUR31bzw_IrnX4zRJ6G3Wx?usp=sharing

# Installation

    $ pip install nn-for-dummies

# Usage

    model = nn.Model(
        nn.Layer(size=(4,5), activation='Relu'),
        nn.Layer(size=(5,3), activation='Relu'),
        nn.Layer(size=(3,10), activation='sigmoid'),
        nn.Layer(size=(10,6), activation='ReLU'),
        nn.Layer(size=(6,1), activation='ReLU')
    )

    # import and preprocess data
    x,label = Data.get_data("data_banknote_authentication.csv")
    x = Data.normalize(x)
    X_train, X_test, label_train, label_test = Data.split_data(x,label)

    # Train the model
    model.fit(X_train,label_train,'SGD','MSE',alpha = 0.0001,epoch = 15,graph_on = True)

    # evaluate the model
    [accuracy,f1_score,confusion_matrix] = model.evaluate(X_test,label_test,metric = ['accuracy','f1 score','confusion matrix'])
    print(f"accuracy: {accuracy}")
    print(f"f1_score: {f1_score}")
    print("confusion matrix:\n",confusion_matrix)

    model.save()



