Machine Learning

MakinaRocks Unveils ‘Link’

MakinaRocks

Link enhances the usability of JupyterLab, offering more readable pipelines and improved collaboration while eliminating Kubernetes’ technological hurdles.

MakinaRocks, an AI-based startup specializing in manufacturing and industrial solutions, today launched a community version of its AI and Machine Learning (ML) modeling tool MakinaRocks Link™ (hereafter referred to as “Link”), making their industry-changing technology available for a wider variety of Machine Learning Operations (MLOps) environments.

Link is an extension for JupyterLab – an interactive development interface for notebooks, code, and data – that lets users easily create readable pipelines for AI and ML modeling. Link maintains the usability of JupyterLab that data scientists rely on while removing technological hurdles related to Kubernetes, a portable, open-source platform for managing workloads and services. By removing the technological hurdles associated with Kubernetes, Link allows users to create pipelines that can be used in MLOps environments with ease, even without a working knowledge of Kubernetes.

Link offers a number of exciting features that will streamline workflows and dramatically improve the experience for those working with JupyterLab. First, Link users can now define relationships between different cells and their execution sequence, a feature that has been missing from JupyterLab until now. Link makes that possible by creating a pipeline in the code script screen to increase the readability of notebook code. It also comes with additional features such as pipeline execution, comment writing, header color changing capabilities, and component storage and sharing – all features designed to simplify pipeline configuration and usage.

Second, Link helps eliminate repetitive tasks and boost productivity by caching the results of executed cells. Cache data storage and sharing features enable a seamless, collaborative workflow, while simplifying workflow reproduction for other collaborators.

Third, Link makes collaboration among data scientists easier and more efficient. The very nature of JupyterLab’s built-in flexibility makes it challenging to use different approaches to reuse other users’ output. Link helps overcome this difficulty, promoting the reusability of code and keeping collaborators on the same page by allowing them to store and share execution results and pipelines, all or in part. Link also supports diverse collaboration features such as commenting, component grouping and Python script conversion.

Additional features such as the management of pipelines, management of change history for notebook source code and execution environment synchronization will be added in the coming months. Link is available for free download, with further product details on its official website (link.makinarocks.ai).

 “MakinaRocks is a startup that has been solving various problems in the manufacturing and industrial sectors through AI solutions since its inception,” said co-CEO Andre S. Yoon. “We’ve launched Link to help solve the problems data scientists experience in their daily work environment. Link will offer improved AI and ML modeling experiences for data scientists with its diverse features and help overcome JupyterLab’s limitations while further enhancing its strengths.”

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