Metadata-Version: 2.1
Name: lightwood
Version: 0.18.0
Summary: Lightwood's goal is to make it very simple for developers to use the power of artificial neural networks in their projects.
Home-page: https://github.com/mindsdb/lightwood
Author: MindsDB Inc
Author-email: jorge@mindsdb.com
License: MIT
Download-URL: https://pypi.org/project/lightwood
Description: <h1 align="center">
        	<img width="400" src="https://mindsdb.github.io/lightwood/assets/logo.png" alt="Lightwood">
        	<br>
        	<br>
        </h1>
        
        [![Build Status](https://travis-ci.org/mindsdb/lightwood.svg?branch=master)](https://travis-ci.org/mindsdb/lightwood)
        ![](https://img.shields.io/badge/python-3.6%20|%203.7|%203.8-brightgreen.svg)
        [![PyPI version](https://badge.fury.io/py/lightwood.svg)](https://badge.fury.io/py/lightwood)
        ![PyPI - Downloads](https://img.shields.io/pypi/dm/lightwood)
        [![Discourse posts](https://img.shields.io/discourse/posts?server=https%3A%2F%2Fcommunity.mindsdb.com%2F)](https://community.mindsdb.com/)
        
        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](https://mindsdb.github.io/lightwood/API/).  
        
        ## Try it out
        
        ### Installation
        You can install Lightwood from pip:
        
        ```python
        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](https://mindsdb.github.io/lightwood/API/) from Lightwood
        ```python
        from lightwood import Predictor
        ```
        
        Train the model.
        ```python
        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.
        
        ```python
        prediction = sensor3_predictor.predict(when={'sensor1':1, 'sensor2':-1})
        ```
        
        * You can also try Lightwood in Google Colab: [![Google Colab](https://colab.research.google.com/assets/colab-badge.svg "Lightwood")](https://colab.research.google.com/drive/10W43sur_uj28ROiGuAIF9X46_Xrx1e7K)
        
        ## Contributing
        Thanks for your interest.There are many ways to contribute to this project. Get started [here](https://github.com/mindsdb/lightwood/blob/master/CONTRIBUTING.md).
        
        ## License ![PyPI - License](https://img.shields.io/pypi/l/lightwood)
        
        * [Lightwood License](https://github.com/mindsdb/lightwood/blob/master/LICENSE)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: full
