Amazon is sponsoring a hackathon where you will get a chance to bring your ideas to reality, and create a future which helps with augmenting human intelligence. In the process you will learn the end-to-end process of building machine learning (ML) models. You will learn how to apply pre-trained ML API services to a wide spectrum of business and project challenges. You will then learn how AI/ML enabled devices are making it easy for developers to get started with deep learning and other forms of ML. Finally, you will learn how to building, train, and deploy ML models for scale using Amazon SageMaker, a fully-managed service covering the entire machine learning workflow. Prizes will be awarded to 1st, 2nd, and 3rd place winners.
Important Dates:
Registration deadline: Friday November 1, 2019
Team announcements and hackathon dates: Thursday November 8, 2019, or sooner Hackathon: November 8 – 17, 2019
Winner announcements: November 25, 2019
Presentation to AWS leadership: January 2020
Themes:
Participants are encouraged to develop project ideas that benefit the following goals, and show how deep learning and computer vision can accelerate our progress towards each goal using the DeepLens platform:
- Increases human productivity
- Increase developer productivty
- ML for Humanitarian
- ML for Earth
- Any other idea which augments and helps human intelligence
Judging:
Projects will be evaluated across 3 criteria:
- Creativity
- Execution
- Simplicty
- Technical Completeness
- Impact
Output:
You will need to deliver a video presentation and the source of your code to your solution.
- Video Presentation:
- 90 seconds that include the problem statement, solution, approach to solution, challenges, and demo.
- Code:
- Your repository must host the .json model definition, model parameter file, lambda function, gist log and Readme file. The Readme file should contain model location and access instructions, step by step instructions on how to use the trained model and lambda functions, references to any other applicable documents or arxiv papers your project is based on, and testing instructions needed for testing your model. If needed for your solution, also include any side scripts or lambda functions needed to test.
Register at https://bit.ly/2o9n6dL
Contact Tara Shankar Jana | Senior Product Marketing Manager | AWS Machine Learning, AI Devices at tarajana@amazon.com if you have questions about logistics (not technical).
Contact Phu Nguyen | Senior Product Manager | AWS Machine Learning, AI Devices at phu@amazon.com if you have technical questions.
Learn more about DeepLens at https://aws.amazon.com/deeplens/