Welcome to KangooML’s documentation!#
Kangoo is a Python framework, as well as a cloud-based repository system and repository standard, to manage machine learning solutions.
It utilizes known tools and platforms like Git, GitLab, Amazon S3, Influx and machine learning frameworks like TensorFlow, PyTorch, Darts and other to simplify everyday work with models and datasets within an organization.
About#
Curious to learn more about our solution? Step inside our About Kangoo section, where we unveil the inner workings, the genesis, and the compelling reasons behind its creation.
Getting started#
Don’t know where to start? Dive into Getting started sections to learn the basics and start right away.
Important concepts#
To make the best use of Kangoo framework, it is important to get acquainted with the structure of GitLab repositories.
Don’t worry - it has been designed to be as intuitive as possible and similar to the Python convention.
However, check our Model repository structure section to make sure You don’t miss anything.
Finally, we strongly encourage taking a look at Other section to understand some additional concepts introduced within our framework.
Tutorials#
We’ve created step-by-step tutorials featuring KangooML workflow examples, covering model repository setup and inference.
Code samples#
Take a look at more code samples in Code samples section.
Command Line Interface#
Kangoo is not only a Python package.
During the installation, You also receive kangoo command line tools for both developers and end users.
Check the Kangoo’s Command Line Interface section to learn more.
How do I …?#
Reading technical documentation might be tedious and hard - and we are totally aware of it. In the Kangoo, how do I …? section, we’ve provided a more thorough explanation of the frequently used functionalities. There is quite a good chance that You’ll find there what You are looking for.
Modules#
Would You like to know literally everything? Well, we won’t stop You. Dive into all available modules.