Tensorflow for Social Good

TENSORFLOW FOR SOCIAL GOOD ETHICS SURVEY

Participate in pilot study, build our new programs, and rate TSG. $20 is up for grabs to those who complete all three steps. (E-gift card supplied upon review of data and awarded via random number generator.)

Take Pre-Survey Here

The CITRIS TensorFlow for Social Good program, funded by Google Research, is designed to give undergraduate students a start in TensorFlow, Machine Learning; build camaraderie and teamwork, and add a project to their resumes while developing something of use to society.

TensorFlow for Social Good Program:
  • Learn to use Tensorflow, an industry-grade machine learning technology
  • Work with teams of 2-4
  • Win cool prizes
  • Add a project to your resume
  • Learn skills wanted in the industry
  • Participate in workshops with free food
  • Training led by PhD Candidate Jason He and MS Student Darren Ng
Activities include:
  • Three workshops to learn TensorFlow
  • Network with industry partners and others
  • Ability to work with hundreds of TensorFlow datasets
  • We're having a fun networking part with pizza at the workshop events. Vegan and vegetarian options will be available
  • Build and present a final project with your team and win awards

Important Dates:

  • Applications for Trainer due

  • Participating student signups open

    Sign Up Here

  • First training session

    Add to Calendar
    Room: COB 1 116
    6:00 - Free Pizza and networking
    6:30 - Coding Presentations & Google Colab led by Jason He
    7:00 - Group Coding Jam
    8:30 - Conclude
    Resources
    Download Slides

  • Second training session

    Add to Calendar
    Room: COB 1 116
    6:00 - Free Pizza and networking
    6:30 - AgriFood Object Detection led by Darren Ng
    7:00 - Group Coding Jam
    8:30 - Conclude
    Download Slides

  • Last day to submit your team

  • Third training session

    Add to Calendar
    Room: SSB 130
    6:00 - Free Pizza and networking
    6:30 - TensorFlow Training led by Jason He and Darren Ng
    7:00 - Group Coding Jam
    8:30 - Conclude
    Jason's Slides
    Jason's Resources and Colabs
    Darren's Google Colab 1. Search up Google Colab 2. Select import notebook 3. Drag this downloaded .ipynb into notebook

  • TensorFlow and Tech for Social Good Presentations

    Add to Calendar
    Room: SSB 130
    5:00 - Team Presentations Start
    6:15 - Scores Tallied
    6:30 - Conclude and Winners Announced
    Download Final Presentation Outline
    Download Judge's Rubric

Prize Categories

One team of 2-4 can win for each category


Frequently Asked Questions
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Bring your laptop, good energy, and make sure to have a Gmail account in order to use Google Colab (you can use anything but we recommend Colab if you're a beginner)

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It's a similar aspect to a hackathon, however, we offer 3 training sessions in which anyone will be able to learn TensorFlow even with no experience! Form a team of 2-4 and present your final project and compete for prizes!
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That's up to you to decide! Make sure it follows CITRIS's core belief in which it is in the interest of society; this means to produce something that will bring good use to today's society, using TensorFlow! Avoid showing an excess amount of your code during final presentations. Demo's should be clear and allow anyone to understand the problem and your solution.
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Come to either the first or second training sessions! There will be plenty of time to collaborate and form a team! Deadline to form a team is 10/20/2022.

Questions? Contact TSG Head Coordinator and CITRIS Web Developer Angelo Fatali, afatali@ucmerced.edu

About The Hosts

Google's mission is to organize the world’s information and make it universally accessible and useful.

CITRIS is committed to transformational experiences for students and training the next generation of leaders in computer science research. We specialize in ag-food-tech, sustainable infrastructures, people and robots, and women in technology.

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.