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.
Learn more from the Lightwood's docs.
You can install Lightwood from pip:
pip3 install lightwoodNote: depending on your environment, you might have to use pip instead of pip3 in the above command.
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 PredictorTrain 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:
Thanks for your interest.There are many ways to contribute to this project. Get started here.
