Awesome
<h1 align="center"> <img width="500" src="https://github.com/mindsdb/mindsdb-docs/blob/master/mindsdb-docs/docs/assets/MindsDBLightwood@3x.png" alt="Lightwood"> <br> <br> </h1>
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:
Contributing
Thanks for your interest. There are many ways to contribute to this project. Please, check out our Contribution guide.
Current contributors
<a href="https://github.com/mindsdb/lightwood/graphs/contributors"> <img src="https://contributors-img.web.app/image?repo=mindsdb/lightwood" /> </a>Made with contributors-img.
