mhmohona / microsoftml-projectshowcasing

A repository to keep all open sources projects that created by individuals or study groups of Microsoft ML Scholarship

Microsoft Azure Machine Learning Scholarship Project Showcasing Challenge

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 🖼

Winners:

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

• Chest X-ray Image Classification for COVID-19 and Pneumonia using Deep CNN

Timeline:

Start date: 28 August 2020, 00.01am UTC
End date: 20 September 2020, 11.59pm UTC
Result Announced: 25 September 2020

Rules:

• 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.

Submission:

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.

Guidelines:

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:
  • Free Azure Account
  • Free Azure for Students
  • Free Azure Studio Classic

Evaluation criteria:

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.

Judges:

The Microsoft Azure Project Showcase Committee (see members below) will serve as judges for this showcase challenge.

Winners:

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

Prize:

Winning team will be provided Badges.
Winner group name will be showcased on the Google Site.

Note about organizing team:

The members of the organizing team cannot participate in this challenge.

Organizing team:

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.