AWS rolls out SageMaker Studio Lab, a free ML service for beginners

Amazon Web Services on Wednesday unveiled SageMaker Studio Lab, a free version of Amazon SageMaker — an AWS service that helps customers build, train, and deploy machine learning models. Designed for machine learning beginners, users can try out SageMaker Studio Lab without an AWS account, credit card, or any knowledge of cloud configuration.

Distinctive feature

Managing artificial intelligence and machine learning in the enterprise

Managing artificial intelligence and machine learning in the enterprise

AI and machine learning deployments are in full swing, but for CEOs, the biggest issue will be managing these initiatives, figuring out where the data science team fits and what algorithms to buy versus build.

Read more

Studio Lab is currently available in public preview.

The service is based on the open source JupyterLab and provides free access to AWS account resources. To get started, the user creates an account (separate from the AWS account) and chooses whether they need a CPU or GPU instance for their project. The service provides 12 hours of CPU or four hours of GPU per user session, with an unlimited number of user sessions available.

Users get at least 15 GB of persistent storage per project. When the session ends, Studio Lab will take a snapshot of the environment, so users can pick up where they left off.

AWS SageMaker is using Studio Lab to launch the AWS Disaster Response Hackathon, which aims to inspire ideas for using machine learning to address challenges related to natural disaster preparedness and response. The hackathon runs until February 7, 2022, and offers prizes worth $54,000. AWS is also trying to set a Guinness World Record for the “Biggest Machine Learning Competition”.

Meanwhile, AWS is also launching a new $10 million scholarship to help students pursue careers in machine learning and To the. The AWS Artificial Intelligence and Machine Learning (AWS AI & ML Scholarship) program is designed to serve underserved and underrepresented high school and college students in the field.

It uses the new AWS DeepRacer and AWS DeepRacer Student League to teach students foundational machine learning concepts.

Up to 2,000 eligible students will win a scholarship for AI programming with the Python Udacity Nanodegree programme. Five hundred students with the highest grades in the first Udacity Nanodegree program will receive a second Udacity Nanodegree scholarship on Deep Learning and Machine Learning Engineering. These top 500 students will also have access to mentorship opportunities from Amazon and Intel technology experts for career insights and advice. The program will also provide free access to dozens of hours of free training on machine learning models and learning materials.

Latest articles

Related articles

Leave a reply

Please enter your comment!
Please enter your name here