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 is like Legos for Machine Learning, with two objectives:
- Make it so simple that you can build predictive models with a line of code.
- Make it so flexible that you can change and customize everything.
Lightwood runs on Pytorch and gives you full control of what you can do.
Documentation
Learn more from the Lightwood's docs.
Quick start
pip3 install lightwood
Learn
You can train a Predictor as follows:
from lightwood import Predictor
sensor3_predictor = Predictor(output=['sensor3']).learn(from_data=pandas.read_csv('sensor_data.csv'))
Predict
You can now given new readings from sensor1 and sensor2 predict what sensor3 will be.
prediction = sensor3_predictor.predict(when={'sensor1':1, 'sensor2':-1})
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
lightwood-0.15.8.tar.gz
(55.9 kB
view details)
File details
Details for the file lightwood-0.15.8.tar.gz.
File metadata
- Download URL: lightwood-0.15.8.tar.gz
- Upload date:
- Size: 55.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6bf43bde1a1b3f9f2a8be3cf76ce076fa20083a8ec009fb8a87cd55a0536e7f9
|
|
| MD5 |
c63476b0aaadac4b3282e02898a1c6b0
|
|
| BLAKE2b-256 |
91c4f537c9d86dcd55b61c355a7ac779268b1635fae426e465a6c6b10783af6c
|
