- Cash Prize: $ 5,000.00
Training Data on the Seattle Spheres: Link to Come
Amazon SageMaker is a fully-managed machine learning platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker includes the most common machine learning algorithms and is also pre-configured with the latest versions of frameworks such as TensorFlow and Apache MXNet.
NVIDIA GPUs along with the CUDA-X AI libraries are supported on AWS EC2 P & G instances as well as AWS SageMaker for Training & Inference. NVIDIA GPUs are the most widely adopted platform for DL training and the most performant for real-time inference, and accelerate all deep learning frameworks. This complete platform saves data science researchers and developers time and money, letting them bring next-generation AI-powered services to life.
Each attendee will receive $100 AWS credits to build out their solutions. Make sure to create an AWS Account before you arrive.
Each submission will be scored in each round based on the following criteria with a minimum score of 0 and maximum score of 20 points, with the final score being the average of the judges’ scores:
All developers, designers and entrepreneurs who are 18 and over.
Teams can be created in advance using the Environmental Hackathon Slack channel and/ or onsite and will be comprised of 1 to 5 individuals.
Judging will have one or two rounds, depending on the number of projects, each with a live presentation format without slides or pitch decks.
All code developed as part of the Environmental Hackathon event must be fresh. Before the start of the hackathon, developers can create wireframes, designs and user flows. They can also come with hardware. But to keep things fair, all code must be written onsite at the hackathon. Other than that, almost anything goes and you can use any coding languages or open-source libraries.