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ML-DL-Models


ML-DL-Models is library to integrate various pre-trained Machine Learning and Deep Learning to your project through ml-dl-models api link.

Usage


In the following paragraphs, I am going to describe how you can get and use ml-dl-models for your projects.

Getting it

To download ml-dl-models, either fork this github repo or simply use Pypi via pip.

$ python -m pip install --upgrade pip
$ pip install ml-dl-models

Using it

ML-DL-Models was programmed with ease-of-use in mind. First, import models from it.

from ml_dl_models import MelodyGenerator

Now you are ready to create an Melody from a MelodyGenerator model.

data = {'keys':'c d e', 'default':True}
path = '/home/LaxmanMaharjan/melody.mp3' # default value is 'melody.mp3' in same directory.
mg = MelodyGenerator(data = data, path = path)
mg.generate_melody()

You can also get the cached notes(notes that are already fetched to model) from Melody Generator.

mg = MelodyGenerator()
print(mg.get_cached_notes)

You can instantiate MelodyGenerator class with default value of data and path.

mg = MelodyGenerator()
mg.generate_melody()

Note: If you use default value of data and path to instantiate MelodyGenerator class than data is chosen from one of the values from cached data.

Learn more about Data Representation link

Metadata

Release files for ml-dl-models 1.0.3

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

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Source distribution for ml-dl-models 1.0.3
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Table of built distributions (wheels) for ml-dl-models 1.0.3
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ml_dl_models-1.0.3-py3-none-any.whl Python 3 none any Details

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Release files / ml_dl_models-1.0.3.tar.gz

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