A challenge to keep and showcase all the open sources projects that are implemented from individual or study groups of Microsoft Azure Machine Learning Scholarship from Udacity.
For whom: Individuals or study groups
3D Virtual Gallery of All Projects: Check here 🖼
Overall Winners:
- 1st Position - Sales Forecasting Using Azure ML
- 2nd Position - Quote Finder
- 3rd Position- Algorithmic Trading
Category Winners
- Category : Using Azure for Implementation based on Course Material - Book Recommendation System
- Category : Using Azure for Implementation based on Course Material - Reduce Employee Attrition
- Category : Innovation & Creativity - Computer Vision for Automate the Process of Elections
- Category : Project Implementation - Viral vs Bacterial Pneumonia Image Classification using Transfer Learning
- Category : Impact & Potential - Predicting Heart Failure with Machine Learning
- Category : Responsible AI - Fake News Classifier using Machine Learning
Community Choice Awards
- Category : Innovation - Decision Intel Foresights MLSecOps Automation MICROSERVICE
- Category : Positive Impact - Predicting Heart Failure with Machine Learning
- Category: Presentation - Algorithmic Trading
Special Mention
Start date: 28 August 2020, 00.01am UTC
End date: 20 September 2020, 11.59pm UTC
Result Announced: 25 September 2020
- Knowledge gained from the coursework must be implemented.
- Project must have been created during the Azure scholarship period.
- Registration form must be completed.
- Project must be submitted before the deadline.
- One can participate in multiple projects.
- Project members' names should be clearly mentioned in the project proposal.
- Make sure your submission is in usable format, as it will be accessed by the judges.
- All projects submitted to this competition must record original work which has not been done or used previously. Plagiarism is - grounds for disqualification.
Participants must submit the following materials:
- Project proposal: Markdown file (ReadMe.md) which explains the project and the team: Team members’ name; what the project does; who the project is for; used technology, etc.
- Project Implementation: Juyter notebook and/or pdf file and/or Presentation video (1 to 3 minute) pitch.
Please structure your submission using the following steps:
- Create a directory with your slack username in the project folder. If you're new to GitHub, you can follow this tutorial by @jhonatantirado
- For implementation, include a Jupyter notebook (if you are using) or a report (in pdf format) that demonstrates a run of your code showing printed output, graphs, etc.
- Structure your code into one or more modules in that directory
- Code should be well-documented. This will help viewers to understand why and what you have done.
- If you are using Jupyter notebook please make sure about the following points:
- Code cells in the notebook should only call functions defined in your modules. Please do not include any actual code logic in the notebook itself.
- The notebooks should be well-documented. Ideally, each code cell should be preceded by a Markdown cell describing why you have included the code cell. It can also include comments on the output generated, eg. describing features of a graph. These text cells should be more high-level than actual code comments, describing the narrative or thought process behind your steps.
- If you are not able to finish the code by the deadline, include your idea, design and implementation strategy in the report.
- If you are using Azure ML Designer: add the screenshots of the design, results, diagrams in the pdf report or Jupyter notebook.
- Free Azure Credits:
Projects will be evaluated based on these criteria:
- Using Azure for Implementation based on Course Material (30%) = Evaluation of how much course material learned in this challenge is implemented in the project.
- Innovation & Creativity (20%) = Evaluation of the novelty, innovation and creativity introduced in the project such that it is appealing.
- Project Implementation (20%) = Evaluation of how much the planned idea was implemented in this project and how well the results are presented.
- Impact & Potential (15%) = Evaluation of the impact that the project may create on society, or for the betterment of technology, humanity or as a business model which solves a major issue.
- Responsible AI (15%) = Evaluation of the potentiality of the project which is fair, inclusive to everyone, preserves data privacy and is secure.
The Microsoft Azure Project Showcase Committee (see members below) will serve as judges for this showcase challenge.
The committee will select 3 overall winners, as well as 1 winner for each of the 5 criteria.
Our community will have a chance to vote for their favorite projects. The 3 with the most votes will win the Scholars Choice Award.
- Overall Winners - 3 winners
- Category Winners - 5 winners (1 from each of the 5 category)
- Community Selected Winners - 3 winners
Winning team will be provided Badges.
Winner group name will be showcased on the Google Site.
The members of the organizing team cannot participate in this challenge.
| Name | Slack handle |
|---|---|
| Aron Castro | Aron Castro |
| Laura Truncellito | LauraT |
| Mahfuza Humayra Mohona | Mahfuza Mohona |
| Maulin Gogri | Maulin Gogri |
| Panth Shah | Panth Shah |
| Ruthu S Sanketh | Ruthu |
| Shikhar Chhabra | Shikhar Chhabra |
| Shudipto Trafder | Shudipto Trafder |
| Shuvro Pal | Shuvro Pal |
If you face any problem, or have any confusion, please contact any of the organizers
Participation is not mandatory for scholars.