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

At its re:Invent convention, AWS as we speak introduced SageMaker Studio Lab, a free service to assist builders study machine learning strategies and experiment with the know-how. Studio Lab supplies customers with all the fundamentals to get began, together with a JupyterLab IDE, mannequin coaching on CPUs and GPUs and 15 GB of persistent storage.
In addition, Amazon additionally as we speak launched the AWS AI & ML Scholarship Program. The firm is committing $10 million oer 12 months to this program, which it runs in collaboration with Intel and Udacity. 2,000 college students will obtain Udacity Nanodegree scholarships by this program yearly, along with mentorship from Amazon and Intel workers.
“The two initiatives we’re saying as we speak are designed to open up academic alternatives in machine learning to make it extra broadly accessible to anybody who’s within the know-how,” mentioned Swami Sivasubramanian, Vice President of Amazon Machine Learning at AWS. “Machine learning might be one of the transformational applied sciences of this era. If we’re going to unlock the complete potential of this know-how to sort out a few of the world’s most difficult issues, we’d like the perfect minds coming into the sphere from all backgrounds and walks of life. We need to encourage and excite a various future workforce by this new scholarship program and break down the associated fee limitations that stop many from getting began with machine learning.”
Image Credits: AWS
To get began with Studio Lab, developer can join for a free account, which must get authorised earlier than you should use the service. It’s unclear what the necessities for getting entry are, although.
“Our mission at AWS is to make machine learning (ML) extra accessible. Through many conversations over the previous years, I discovered about limitations that many ML newbies face,” AWS’s Antje Barth writes in as we speak’s announcement. “Existing ML environments are sometimes too complicated for newbies, or too restricted to assist fashionable ML experimentation. Beginners need to rapidly begin learning and never fear about spinning up infrastructure, configuring companies, or implementing billing alarms to keep away from going over finances. This emphasizes one other barrier for many individuals: the necessity to present billing and bank card data at sign-up.”