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"seadiver" is a Python based DeepLearning Framework which maximized its accessibility for DL beginners.

You can start by creating a model in any desired structure with only 3 required arguments. Easily train, predict and visualize your model.

"seadiver" supports 'export' and 'import' function in 'json' format. pip install is available >> "pip install seadiver"

Simple example for usage is like below.

import seadiver

#build a model model = seadiver.model.ANN(input_shape=(1, 784), structure = (100, 100, 100, 10), output="softmax") model.describe() #prints how the model looks

#train model.train(y= TRAIN_BATCH, t= ANSWER_BATCH, learning_rate=0.001, iteration=1000)

#predict model.predict(x = INPUT)

#export model as a 'json' file to a local directory model.export(directory = "C:\Users....", file_name="myModel.json")

#import model from a local directory imported_model = seadiver.factory.make(file = "C:\Users.....\myModel.json")

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Updates on more types of model such as 'CNN', 'LSTM' is underway. Thanks, and please contact the author via e-mail for any comment.

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Release files for seadiver 0.3.6

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for seadiver 0.3.6
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Table of built distributions (wheels) for seadiver 0.3.6
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seadiver-0.3.6-py3-none-any.whl Python 3 none any Details

Total release size: 21.7 kB

Release files / seadiver-0.3.6.tar.gz

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Release files / seadiver-0.3.6-py3-none-any.whl

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