Kedro download for Linux

This is the Linux app named Kedro whose latest release can be downloaded as 0.18.14sourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.

 
 

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SCREENSHOTS:


Kedro


DESCRIPTION:

Kedro is an open sourced Python framework for creating maintainable and modular data science code. Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems. Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems together. Makes a seamless transition from development to production, as you can write quick, throw-away exploratory code and transition to maintainable, easy-to-share, code experiments quickly. Puts the "engineering" back into data science because it borrows concepts from software engineering and applies them to machine-learning code. It is the foundation for clean, data science code.



Features

  • Kedro's pipeline visualisation plugin shows a blueprint of your developing data and machine-learning workflows, provides data lineage
  • Keeps track of machine-learning experiments and makes it easier to collaborate with business stakeholders
  • A series of lightweight data connectors used to save and load data across many different file formats and file systems
  • Supported file formats include Pandas, Spark, Dask, NetworkX, Pickle, Plotly, Matplotlib and many more
  • The Data Catalog supports S3, GCP, Azure, sFTP, DBFS and local filesystems
  • The Data Catalog also includes data and model snapshots for file-based systems


Programming Language

Python


Categories

Frameworks

This is an application that can also be fetched from https://sourceforge.net/projects/kedro.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.



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