GithubHelp home page GithubHelp logo

ghsusanibar / microsoftml-projectshowcasing Goto Github PK

View Code? Open in Web Editor NEW

This project forked from mhmohona/microsoftml-projectshowcasing

0.0 0.0 0.0 191.97 MB

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

Python 0.30% HTML 2.08% Dockerfile 0.01% Jupyter Notebook 97.61% R 0.01%

microsoftml-projectshowcasing's Introduction

challenge

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

Timeline:

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

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:

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.

microsoftml-projectshowcasing's People

Contributors

navergoni avatar mhmohona avatar jhonatantirado avatar iamsdt avatar lourdes95 avatar sayed6201 avatar bvdinesh79 avatar xquyvu avatar hariharan-palanichamy avatar heber-augusto avatar anikchowdhury1 avatar tanglijhu avatar rutujak24 avatar scign avatar gaganmanku96 avatar bhadreshpsavani avatar aarthialagammai avatar waqasne avatar anandece4u avatar arindam-ds avatar basit040 avatar anshutrivedi avatar nandex7 avatar khalidw avatar pogayo avatar ravingalaxy avatar urmee04 avatar polarbeargo avatar dataclip avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.