SnorkelFlow on Ubuntu 26.04 with maintenance support by PCloudhosting

As described on AWS Marketplace.

<p> <b>Snorkel 0.10.0 on Ubuntu 24.04 with Free Maintenance Support by Pcloud</b> </p> <p> Snorkel AI helps enterprises move faster with AI by solving one of the biggest bottlenecks in machine learning labeled data.With Snorkel Flow on AWS, organizations can automate the labeling of massive volumes of unstructured data including text,documents, logs, images, and more accelerating AI development by up to 100x compared to manual labeling. </p> <p> Built for scale and enterprise workloads, Snorkel Flow integrates natively with Amazon S3, allowing teams to seamlessly access existing data lakes. Instead of spending months hand labeling data, data scientists and ML teams can programmatically generate high quality training datasets using labeling functions, weak supervision, and data centric AI techniques. The result is faster model iteration, lower costs and better performing AI systems. </p> <p> <b>Designed for the AWS Ecosystem</b> </p> <p> Snorkel AI fits naturally into modern AWS native architectures. It integrates directly with Amazon Bedrock,SageMaker JumpStart, SageMaker Training, and Amazon EKS, enabling teams to fine tune large language models, train custom ML models, and deploy them at scale all within the AWS ecosystem. </p> <p> Whether you are building NLP pipelines, enterprise search, document intelligence or LLM powered applications, Snorkel Flow provides the flexibility to move from experimentation to production without re architecting your stack. Availability on AWS Marketplace makes procurement simple, secure, and enterprise ready. </p> <p> <b>More Intelligent AI Through Responsible Data Practices</b> </p> <p> Just as environmental awareness is essential when snorkeling in fragile coral ecosystems, responsible data practices are critical when building AI at scale. </p> <p> By reducing repetitive human labeling and centralizing supervision logic, organizations minimize risk, improve consistency and maintain stronger governance over how training data is created and used. This data centric approach helps protect enterprise data assets while still enabling rapid AI innovation. </p> <p> <b>Why Teams Love Snorkel AI</b> </p> <p> Organizations adopt Snorkel AI because it lowers the barrier to entry for advanced AI while still supporting the most demanding enterprise use cases. It is often the first and sometimes the only practical way for teams to unlock value from unstructured data at scale. </p> <p> Much like snorkeling offers a low cost, high impact way to experience the underwater world, Snorkel Flow delivers powerful AI capabilities without the complexity of traditional large scale ML programs. Teams achieve faster results, build better models and reach production smoothly without massive labeling budgets or long timelines. </p> <p> <b>Snorkel AI on AWS gives enterprises a more thoughtful, faster, and more scalable way to build AI that actually works.</b> </p>

Highlighted by the publisher on AWS Marketplace.

Works with any downstream machine learning framework or pipeline.

Create and apply labeling functions to generate large training datasets quickly.

Handles massive datasets and reduces reliance on slow manual labeling.

As stated by the publisher on AWS Marketplace.

no refund