Metadata-Version: 2.1
Name: kxy
Version: 1.4.0
Summary: A Powerful Serverless Pre-Learning and Post-Learning Analysis Toolkit
Home-page: https://www.kxy.ai
Author: Dr. Yves-Laurent Kom Samo
Author-email: github@kxy.ai
License: GPLv3
Download-URL: https://github.com/kxytechnologies/kxy-python/archive/v1.4.0.tar.gz
Project-URL: Documentation, https://www.kxy.ai/reference
Project-URL: Source Code, https://github.com/kxytechnologies/kxy-python/
Description: <div align="center">
          <img src="https://www.kxy.ai/theme/images/logos/logo.svg"><br>
        </div>
        
        -----------------
        
        # Boosting The Productivity of Machine Learning Engineers
        [![License](https://img.shields.io/badge/license-GPLv3%2B-blue)](https://github.com/kxytechnologies/kxy-python/blob/master/LICENSE)
        [![PyPI Latest Release](https://img.shields.io/pypi/v/kxy.svg)](https://www.kxy.ai/)
        [![Downloads](https://pepy.tech/badge/kxy)](https://www.kxy.ai/)
        
        
        ## Documentation
        https://www.kxy.ai/reference/
        
        
        ## Installation
        From PyPi:
        ```Bash
        pip install kxy
        ```
        From GitHub:
        ```Bash
        git clone https://github.com/kxytechnologies/kxy-python.git & cd ./kxy-python & pip install .
        ```
        ## Authentication
        All heavy-duty computations are run on our serverless infrastructure and require an API key. To configure the package with your API key, run 
        ```Bash
        kxy configure
        ```
        and follow the instructions. To get an API key you need an account; you can sign up for a free trial [here](https://www.kxy.ai/signup/). You'll then be automatically given an API key which you can find [here](https://www.kxy.ai/portal/profile/identity/). 
        
        KXY is free for academic use. 
        
        
        ## Docker
        The Docker image [kxytechnologies/kxy](https://hub.docker.com/repository/docker/kxytechnologies/kxy) has been built for your convenience, and comes with anaconda, auto-sklearn, and the kxy package.
        
        To start a Jupyter Notebook server from a sandboxed Docker environment, run
        ```Bash
        docker run -i -t -p 5555:8888 kxytechnologies/kxy:latest /bin/bash -c "kxy configure <YOUR API KEY> && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root --NotebookApp.token=''"
        ```
        where you should replace `<YOUR API KEY>` with your API key and navigate to [http://localhost:5555](http://localhost:5555) in your browser. This docker environment comes with [all examples available on the documentation website](https://www.kxy.ai/reference/latest/examples/).
        
        To start a Jupyter Notebook server from an existing directory of notebooks, run
        ```Bash
        docker run -i -t --mount src=</path/to/your/local/dir>,target=/opt/notebooks,type=bind -p 5555:8888 kxytechnologies/kxy:latest /bin/bash -c "kxy configure <YOUR API KEY> && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root --NotebookApp.token=''"
        ```
        where you should replace `</path/to/your/local/dir>` with the path to your local notebook folder and navigate to [http://localhost:5555](http://localhost:5555) in your browser.
        
        ## Other Programming Language
        We plan to release friendly API client in more programming language. 
        
        In the meantime, you can directly issue requests to our [RESTFul API](https://www.kxy.ai/reference/latest/api/index.html) using your favorite programming language. 
        
        
Keywords: Lean ML,AutoML,Pre-Learning,Post-Learning,Model-Free ML
Platform: UNKNOWN
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Information Technology
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Development Status :: 5 - Production/Stable
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Description-Content-Type: text/markdown
