AWS launches SageMaker Studio Lab, a free tool for learning machine learning

At its re:Invent conference, AWS today announced SageMaker Studio Lab, a free service to help developers learn machine learning techniques and experiment with the technology. Studio Lab provides users with all of the basics to get started, including a JupyterLab IDE, model training on CPUs and GPUs and 15 GB of persistent storage.

In addition, Amazon also today launched the AWS AI & ML Scholarship Program. The company is committing $10 million oer year to this program, which it runs in collaboration with Intel and Udacity. 2,000 students will receive Udacity Nanodegree scholarships through this program every year, in addition to mentorship from Amazon and Intel employees.

“The two initiatives we are announcing today are designed to open up educational opportunities in machine learning to make it more widely accessible to anyone who is interested in the technology,” said Swami Sivasubramanian, Vice President of Amazon Machine Learning at AWS. “Machine learning will be one of the most transformational technologies of this generation. If we are going to unlock the full potential of this technology to tackle some of the world’s most challenging problems, we need the best minds entering the field from all backgrounds and walks of life. We want to inspire and excite a diverse future workforce through this new scholarship program and break down the cost barriers that prevent many from getting started with machine learning.”

Image Credits: AWS

To get started with Studio Lab, developer can sign up for a free account, which needs to get approved before you can use the service. It’s unclear what the requirements for getting access are, though.

“Our mission at AWS is to make machine learning (ML) more accessible. Through many conversations over the past years, I learned about barriers that many ML beginners face,” AWS’s Antje Barth writes in today’s announcement. “Existing ML environments are often too complex for beginners, or too limited to support modern ML experimentation. Beginners want to quickly start learning and not worry about spinning up infrastructure, configuring services, or implementing billing alarms to avoid going over budget. This emphasizes another barrier for many people: the need to provide billing and credit card information at sign-up.”

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