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Berrijam Jam

Are you a machine learning and artificial intelligence story teller?

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Our mission at Berrijam is to bring equity to artificial intelligence by making it simple, accessible and affordable for as many people as possible. Beyond technical innovation, the mission requires bringing together machine learning expertise with the art of storytelling.

 

That's why we created Berrijam Jam!

 

A Berrijam Jam is a competition where teams identify and solve interesting predictive or analytical problems using machine learning. In addition to trophies and bragging rights, there are cash prizes for the top three teams. We are also awarding Innovating Application of AI (IAoAI) awards to teams that didn't place in the top three places but, came up with an innovative application of AI.

 

Berrijam encourages you to think creatively and broadly about where AI & ML can be used.


See Terms & Conditions for the full details of the competitions terms and conditions that participants must agree to.

1

Jam - April 2023

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The first Berrijam Jam was hosted with the University of NSW (UNSW) for students enrolled in COMP9417: Machine Learning and Data Mining. If you are not part of the course or UNSW but are interested in joining future Jams, let us know.

Jam April 2023 Winners

On the Podium

The top 3 winners were graded not only on their technical solutions but also how they crafted a compelling narratives from their discoveries.

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7 - Berry Good

Classification of Breast Cancer in Mammograms

  • Aaleen Ahmed

  • Hamza Jalal

  • Harsh Murali

  • Jaehwi Park

  • Teewin Xiao

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12 - Big Brains

Understanding Airline Satisfaction

  • Hanh Nguyen

  • Jae Hyun Jeon

  • Melissa Priscilla

  • Rafael Dairokuno

  • William Dahl

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8 - NAFT

Mortality Rates of ICU Patients with Heart Failure

  • Anish Saraogi

  • Bertram Chung Lai Lee

  • Frank Yun Li

  • Novin Wijesundara

  • Tanya Hollis

Innovative Applications of AI

The following teams proposed innovative applications of artificial intelligence.

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10 - Passion Fruit

Rice Leaf Disease

  • Daijiao Liu

  • Jiaxu Shi

  • Tong Xia

  • Yanqi Zhu

  • Zhiyue Zheng

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11 - JJCSY

Fake News Detection

  • Cheskene Marwy Tan

  • James Phillips

  • Julia Segarra Robles

  • Seivabel Halim

  • Øyvind Husveg

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9 - Team Spirit

Authorship Identification

  • Duke Nguyen

  • Jaeff Hong

  • Weixian Qian

  • Yu Kong​

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13 - Big Brain Machine Learners

Energy Prediction

  • Ji Hye Kim

  • Lauren Wu

  • Michael Agius

  • Mina Na

  • Oscar Mose

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5 - The last of us

Predict Car Crash Severity

  • Andrea Marie Dobles

  • Christopher Luong

  • Mikkel Endresen

Frequently asked questions

  • What do the teams do?
    Each team identifies a predictive problem and goes through the following steps irrespective of domain or application: Identifying the problem where predictive modeling is needed. Finding, cleaning and preparing relevant datasets. Exploratory Data analysis, feature engineering, modeling and validation. Story-telling & presentation to articulate the value and contribution of their work. At the end of the competition, each team must make a single submission for the whole team. How each team member works is entirely up to each team. One tip to ensure that you tap into each other's talents, diverse perspectives and start collaborating early.
  • Who can Jam?
    Team members must be enrolled in Dr Mohammadi's Machine Learning course at University of New South Wales in S1, 2023. In future Jams, we will consider expanding the competition. If you are interested, send us a message to let us know of your interest, your school or university
  • How many people per team?
    Anywhere between 3 and 5, inclusive. So effectively, 3, 4, or 5.
  • What happens if there is a tie?
    Berrijam’s team will review the submissions and break the tie. The criteria we will use to consider will include: Ease to re-create the findings Quality of documentation Quality of code Commercial use of data There will only be one team for each of the top three respective winning places.
  • What are the prizes?
    The top three teams are awarded a cash prize to be shared amongst the team members. These are: $3000 for 1st place team $2000 for 2nd place team $1000 for 3rd place team In addition to this, Berrijam will award up to 10 Innovative Applications of Artificial Intelligence (IAoAI) prizes of $300 per team, for interesting applications of AI & ML. This is for teams that did not place in the top 3, and so get your creative hats on!
  • I don't have permission to access or upload to the Google Drive folder?
    The submissions are made via Google Drive folders that are specific to each team and assigned permission based on the student specific email provided at the time of team registration. This is typically the email ending in @ad.unsw.edu.au. Some students have mail forwarded to other emails from their @ad.unsw.edu.au and are trying to access the Google Drive from a non @ad.unsw.edu.au email. As a result they do not have permissions to access the folders. Please make sure you use the correct email address to set up a Google Account. The instructions on how to do that are available here: Create a Google Account.
  • What types of problem do teams solve?
    Teams select which particular problem they want to tackle using AI & ML. The problem must be formulated as of one of five types: 1. Yes or No - a 2-class classification problem. 2. How Much - a regression problem. 3. What Next - a recommendation problem. 4. When - time or duration based prediction 5. What's Odd - anomaly detection. The problem can be from any domain or application. Keep in mind creative applications are encouraged. So go broader than the standard business applications of predicting churn. Think about how we can use ML to predict things in architecture, manufacturing, biology, medicine, education, sports, environment, etc.
  • How is a team submission judged?
    Submissions are judged on multiple criteria including: Storytelling - presentation and storytelling are vital for machine learning experts in a professional setting Novelty - is this an interesting and exciting application of machine learning Technical execution - sound and structured approach to model and validate the results Validation of submission in terms of: Ease to re-create the findings Quality of documentation Quality of code
  • What goes in a submission?
    A team can make as many submissions as they want until the deadline. Only the final submission will be considered. A submission must contain: A 2-minute or less video of their project explaining the problem, why it matters and how they solved it using machine learning or what they discovered using machine learning. Presentation slides if any used in the video. Data including license of sourced data and link to the source. Jupyter Notebooks or scripts with python or other scripts (SQL, bash, etc) Documentation that outlines the analytical details, methods, results and conclusions. Instructions to recreate their findings if not already part of documentation.
  • What happens to videos and presentations after the competition?
    The presentation videos from the top three place winners and innovative application of artificial intelligence (IAoAI) awards will be published on Berrijam’s website for other participants to learn from them, as well as promote the competition in subsequent years. This also gives award winners a way to highlight their achievements on their personal websites, resumes or LinkedIn.
  • Updated: How do I make a submission?
    Each team makes a submission using a Google Drive folder dedicated for that team. Only those team members have permissions to access the folder. Each team would have received an email that says "Berrijam Jam shared a folder" and "Berrijam Jam has invited you to contribute to the following shared folder". If you don't see it in your email, check your spam folder. Remember to make sure that you use the email you used to register the team, and not the email that you forwarded. Otherwise you will face permission issues as described in this FAQ question. The steps are: Check your email for the shared folder invitation. Sign up for Google Account using the registration email you provided. See "Create a Google Account" using Existing Email. Access the folder. Read the Readme file in that folder for all that needs to be submitted. Upload the necessary files And you are done.
  • What are the key dates?
    Registration - Complete the entry form, nominating between three to five eligible team members by 5pm AEST 12 March 2023. Final Submission - Make a Submission for the team by 5pm AEST 14 April 2023. Award Ceremony - Winners will be announced on 21 April 2023. (Time and Location is to be confirmed).
  • Can I use data from an expired or inactive competition?
    As long as the data license allows for commercial use, you can use data from past competitions or competitions no longer active. Just check out the other FAQ around data and license requirements to make that assessment.
  • What are the data licenses are allowed?
    An important part of data scientists job is to ensure the data they use adheres to licenses and rules for the organisation producing the data. You should ensure that any data sources are available for commercial use, as per the rules of the competition. Common licence types such as Creative Commons or Open Data Commons have options that allow for the data to be used for commercial purposes, sometimes with additional conditions such as attribution or providing the same licence to others. Its important to check each data source for what licence or terms it falls under and to look for additional conditions. Just because a source is described as an open data source does not give you commercial usage rights. For example both UNICEF and the WHO do not allow commercial use of its data without permission (see their terms here and here). Private data collections also sometimes restrict commercial use, such as on Glassdoor. On the other hand, you can use the data from sources such as data.gov.au, or data.gov.uk. If there is no licence, then you won’t be able to use the data source. As a general guide, avoid licences marked as ‘NC’ or non-commercial. All other Creative Commons or Open Data licences generally allow commercial use. A useful description of common data licences can be found here: https://www.kaggle.com/general/116302 Remember that each submission must include the data and its data license. It is your job to ensure the data used meets the competition requirements.
  • Can I use <some_specific_name> kaggle dataset?
    If you are using a dataset from Kaggle you must read the rules or conditions around the use of the dataset to ensure they allow commercial use. You can do that yourself by reading the rules around that Kaggle competition and reading the data sections. Here are two examples of where the use of the dataset for commercial use is not allowed and so will not be suitable for Berrijam Jams. Example #1: A. Data Access and Use. Unless otherwise restricted under the Competition Specific Rules above, after your acceptance of these Rules, you may access and use the Competition Data for the purposes of the Competition, participation on Kaggle Website forums, academic research and education, and other non-commercial purposes. Example #2: A. Data Access and Use. Unless otherwise restricted under the Competition Specific Rules above, you may access and use the Competition Data for non-commercial purposes only, including for participating in the Competition and on Kaggle.com forums, and for academic research and education. As you can see in both cases the dataset cannot be used for commercial uses, and so are not suitable for Berrijam Jam. You can typically find the rules associated with Kaggle datasets/competitions on the 'Rules' tab. Remember, you to look beyond Kaggle. Here is a list of public datasets that you might find useful. https://github.com/awesomedata/awesome-public-datasets Again, always check the rules of the dataset to allow for commercial use.
  • What data can I use?
    You must find the right data for the problem you want to solve. You will need to hunt for data, a job that most data scientists have to do every day. IMPORTANT: Also the data MUST be 'structured' or tabular. If you want to use unstructured data (images, audios, videos, etc), you must transform it to a structured form and include the scripts/code used to generate it as well as the unstructured and structured format. VERY IMPORTANT: You must ensure the data source license conforms to the competition requirements. It is your job to verify and confirm that. Here are a few pages that link to data source repositories, that might want to consider. But don't limit yourself to just these. Find the data for your problem. 50 Best Open Data Sources Ready to be Used Right Now (2019) - https://learn.g2.com/open-data-sources 55 Free Open Data Sources You Should Know (2022) https://data-ox.com/55-free-open-data-sources-you-should-know-for-2021/ Open Source Data (2023) - https://www.lido.app/post/open-source-data 70 Free Open Source Data Sources (2022) - https://www.octoparse.com/blog/big-data-70-amazing-free-data-sources-you-should-know-for-2021 Another list (2022) - https://www.freecodecamp.org/news/https-medium-freecodecamp-org-best-free-open-data-sources-anyone-can-use-a65b514b0f2d/
  • Help! I have a question. How do I contact Berrijam Jam?
    If you have questions, this is what you should do. Review the FAQ here, and see if we have already answered your questions. We might just respond with the same answer and you'll end up waiting unnecessarily. Email jam@berrijam.com - Note that you might not get an answer for 24 hours. We'll do our best, but there might be other things or lots of other questions/emails. Each time we answer a question that is being asked by others we'll also update the FAQ. Ask Prof. Mohammadi and her team for help with anything technical. Keep in mind that we won't tell you how to solve a particular machine-learning problem, or provide a solution that might give one team an advantage over another. It's a friendly competition after all :)
  • What is the Code of Conduct?
    All participants are expected to abide by the following Code of Conduct.
  • How and where do I attend AI - Talks?
    Accessibility matters, therefore you can attend AI Talks: In person at CBRIN Offices - Level 5, 1 Moore Street, Canberra, ACT or Online via video conferencing - https://berrijam.whereby.com/ai-talks
  • Is the event free? Where can I register?
    Although the event is free, we do require people to register so that we can plan the venue and hosting. Please register here
  • Whats the date and time for the next AI Talks?
    AI Talks is held every 2nd Thursday of the month, 12:30 pm - 1:30 pm Australian Eastern Standard Time.
  • Where can I find parking if I choose to attend at the CBRIN Offices?
    For those attending in person, parking is available at the City West Carpark on Allsop Street. There is also limited street parking around the building.
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