Machine Learning Hackathon In Association With AWS


MachineHack in association with Amazon Web Services brings to the ML community an exciting way to showcase both AWS and Machine Learning skill sets. This hackathon enables the participants to pick any problem of their choice and solve it using the wide range of services offered by AWS.

The participants will be judged based on their background, usage of AWS services, and the problem they solved. The submissions will be classified into 3 buckets in terms of difficulty level (LOW, MEDIUM, HIGH), and winners are picked from all these 3 buckets to ensure that the newcomers who solve relatively easier problems are not left behind when pitted with experienced complex problem solvers. That said, teams who solve some hard problems are quite welcome!


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Why Should You Participate

 The participants will not only get to choose a theme of their choice but also get to showcase and test their AWS skills, which are considered as the industry standard for many ML-based services across the world.

 The core idea of this hackathon is to explore a wide range of AI and ML services AWS provides, which can help to build intelligent applications with out-of-the-box pre-trained language and computer vision services.

 Popular AWS Services:

Developers can use application services by AWS to plug-in pre-built AI functionality into your apps without having to worry about the machine learning models.

  • Build language and vision apps using APIs such as Amazon Comprehend, Amazon Transcribe, Amazon Polly, Amazon Lex, Amazon Translate, and Amazon Rekognition to gain customer insights, personalised content recommendations, and much more! 
  • Leverage Amazon SageMaker to build, train, and deploy machine learning models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high-quality models.
  • Explore Amazon Kendra, to use enterprise search service that’s powered by machine learning.
  • Use AWS Lambda to run the code and business logic for your intelligent application. Using Lambda with machine learning services by AWS enables a server-less architecture, meaning you can run the application without having to manage, scale, or operate any servers or infrastructure. 

Amazon Web Services (AWS), has been the industry leader in the cloud segment for over a decade. Today, it offers tools that bring computer vision, natural language processing, speech recognition, text-to-speech, and machine translation within the reach of every developer.

Steps to Participate

This hackathon doesn’t have a predefined problem statement and dataset. You are free to choose any problem statement but must make use of popular AWS services.

Please follow the below steps after you register for this hackathon

  • Once registered, please log in to AWS to avail the free tier subscription offered by AWS
  • To avail the $20 AWS credits, send us an email at with a detailed problem statement based on your theme of choice and the details of respective team members.
  • Refer the submission requirements provided in the hackathon rules tab to understand the format and mail it to before the deadline


  • One account per participant/team. Submissions from multiple accounts will lead to disqualification.
  • The submission limit for the hackathon is 1
  • All registered participants are eligible to compete in the hackathon.
  • We ask that you respect the spirit of the competition and do not cheat.

Hackathon Specific Rules

Participants are subject to the Generic Rules mentioned above unless otherwise, a contradicting rule is present in the Hackathon Specific Rules mentioned below

Points To Remember

  • AWS Credits: $20 for each team
  • A maximum of 150 teams will be provided with $20 AWS credits each
  • After 150 teams, each team member will have to use the free $100 AWS credits provided with the free tier
  • Team Capacity: 1-4 participants
  • Prerequisite: This Hackathon is only for Working Professionals.
  • Submission: The last date of submission is 20th August 2020

 The participants are expected to choose from the following themes but are not restricted to:

  • Deep Learning, Computer Vision and Image Processing
  • Machine Learning for Automation
  • Machine Learning for DevOps
  • AI with IoT and edge computing
  • Machine Learning for Medicine and Health Care
  • Machine Learning to fight against any pandemic, like COVID
  • AI for Transportation/Media & Entertainment/e-Commerce/FinTech

Submission Requirements

  • MachineHack submission portal should not be used for making the submissions
  • The submission (Only one submission per team) in the specified format should be mailed to before the deadline
  • A 5-slide PDF including the executive summary of your solution, the experiences & skills of all the team members
  • Highlight the AWS services being used (not only AI/ML related services but everything which are being used in the solution)
  • Include a link to the application code on GitHub or BitBucket. The code repository may be public or private. If the repository is private, access must be given in the testing instructions provided with your submission. The code will be used only for application review and testing.
  • The repo should have with adequate information for the reviewer


This hackathon does not support a leaderboard. The winners will be announced once the hackathon is completed.

  • Innovativeness of the solution – 30% – How original & creative is the application
  • Business potential – 30% – How well does the application solve the use case, is the application scalable, how economically viable is the application
  • Integration of AWS services – 40% – How much are you using AWS services to develop your solution


Top 3 teams from each difficulty level (low, medium, high) will be selected and a winner will be picked from each level.

  • Level 3 (high)- Amazon Vouchers worth 20,000 INR
  • Level 2 (medium)- Amazon Vouchers worth 16,000 INR
  • Level 1 (low)- Amazon Vouchers worth 12,000 INR
  • All 3 winning team members will be provided with a participation certificate

More Great AIM Stories

Amal Nair
A Computer Science Engineer turned Data Scientist who is passionate about AI and all related technologies. Contact:

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