Skip to main content

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

Lightwood Actions workflow PyPI version PyPI - Downloads Discourse posts

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. Get started here.

License PyPI - License

Project details


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-0.33.0.tar.gz (72.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

lightwood-0.33.0-py3-none-any.whl (108.7 kB view details)

Uploaded Python 3

File details

Details for the file lightwood-0.33.0.tar.gz.

File metadata

  • Download URL: lightwood-0.33.0.tar.gz
  • Upload date:
  • Size: 72.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.8

File hashes

Hashes for lightwood-0.33.0.tar.gz
Algorithm Hash digest
SHA256 243c9a55b7399e93c892b271176b9c0d6170eae6a92169ace094dbb360484637
MD5 ff6388f666946976c5df539734b06984
BLAKE2b-256 2f8def25dacac21b80d7af17cd882e2f73d8f5cf8a71314fa0c458534ed96ada

See more details on using hashes here.

File details

Details for the file lightwood-0.33.0-py3-none-any.whl.

File metadata

  • Download URL: lightwood-0.33.0-py3-none-any.whl
  • Upload date:
  • Size: 108.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.8

File hashes

Hashes for lightwood-0.33.0-py3-none-any.whl
Algorithm Hash digest
SHA256 cd4218bd110883d2df22773072a267f4eb5b0d01e01714e83bc8b9de5ab8a629
MD5 843648718060871d0473a9400c7a82e5
BLAKE2b-256 211beaceb3419359f0ff7ce688d32a93afc439dbef13b5b15f184530ceec266a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page