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Lightwood's goal is to make it very simple for developers to use the power of artificial neural networks in their projects.

Project description

Lightwood

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Lightwood is like Legos for Machine Learning.

A Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glued together seamlessly with one objective:

  • Make it so simple that you can build predictive models with as little as one line of code.

Documentation

Learn more from the Lightwood's docs.

Try it out

Installation

You can install Lightwood from pip:

pip3 install lightwood

Note: depending on your environment, you might have to use pip instead of pip3 in the above command.

Usage

Given the simple sensor_data.csv let's predict sensor3 values. | sensor1 | sensor2 | sensor3 | |----|----|----| | 1 | -1 | -1 | | 0 | 1 | 0 | | -1 |- 1 |1 |

Import Predictor from Lightwood

from lightwood import Predictor

Train the model.

import pandas
sensor3_predictor = Predictor(output=['sensor3']).learn(from_data=pandas.read_csv('sensor_data.csv'))

You can now predict what sensor3 value will be.

prediction = sensor3_predictor.predict(when={'sensor1':1, 'sensor2':-1})
  • You can also try Lightwood in Google Colab: Google Colab

Contributing

Thanks for your interest. There are many ways to contribute to this project. Please, check out our Contribution guide.

Current contributors

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License PyPI - License

Project details


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