General Information
After you register your details in this website, the links for both challenges will be shared with you. Registered participation must be in teams of 3 students.
Challenge 1: Where there's code, there's bug
So you’ve got a bug in your code? How in the world do you find the thing?
Programming can be quite a roller coaster. There will be times when everything goes well, the code flows out of your fingertips and compiles and runs how it’s supposed to. But there will inevitably also be situations where your program just doesn’t do what you want it to do and the error seems impossible to find. You encountered a bug.
Many techniques have been developed over the years to automatically find bugs in software. Often, these techniques rely on formal methods and sophisticated program analysis. While these techniques are valuable, they can be difficult to apply, and they aren't always effective in finding real bugs. Bug patterns are code idioms that are often errors.
Debugging is an important aspect for developers. Most of the time it is a silly mistake that is overlooked. And once the issue is figured out, it feels like a big mystery is solved.
In this competition, you would be provided with 5 lines of code for each data point and your aim would be to predict whether the middle (line 3) line has a bug or not. 2 lines of code on top and bottom are additionally provided for context. The following diagram could give a symbolic representation of the code column.
Challenge 2: Reddit Science Comments
The goal of the competition would be to create a model that can accurately classify the Reddit comments in to three different topics (physics, chemistry, and biology) categories.
To participate in the competition, you would need to develop a machine learning model and use a set of labeled Reddit comments to train it.
The labeled comments would include the text of the comment and the corresponding label (physics, chemistry, or biology). You could then use this trained model to make predictions on a set of unlabeled Reddit comments, which you would submit to the competition organizers. The organizers would then evaluate the accuracy of your model's predictions and rank the submissions based on their performance.
There are many different approaches you could take to develop a machine learning model for this task. One approach would be to use a natural language processing (NLP) technique, such as a convolutional neural network (CNN) or a recurrent neural network (RNN), to analyze the text of the comments and make predictions based on the words and phrases used in the comments. Another approach could be to use a machine learning technique such as support vector machines (SVMs) or decision trees to classify the comments based on certain features or characteristics of the text.
It's worth noting that this type of machine learning competition would likely be quite challenging, as accurately classifying text into specific categories can be difficult due to the complexity and variability of natural language. It would require careful preprocessing of the text data, as well as careful tuning of the machine learning model to achieve good performance.
Rules
It's important to carefully review the rules of any machine learning competition you participate in to ensure that you understand the requirements and are able to comply with them:
- The competition ends on the 24nd of January 2022 at 11:59 PM (Dubai time) 7:59 PM UTC
- Participants must be in teams of 3 students.
- Participants must register in both the competition website (This website) and the competition platform (Kaggle).
- The participants must use the competition platform (Kaggle) to train the model and submit the predicted labels and code. (A brief tutorial is provided below)
- Participants will be evaluated based on the evaluation metric of the challenge and the total time required to train and test the model.
- Participants must use the provided labeled training data to train their models through the competition platform.
- The organizers may disqualify submissions that do not follow the rules or that exhibit inappropriate behavior.
- The organizers may provide additional resources, such as sample code or tutorials, to help participants get started.
Prizes & Rewards
The winners will be announced during the AI week event on 26th of January 2023.
Challenge 1:
- First prize 800 AED.
- Second prize 600 AED.
Challenge 2:
- First prize 800 AED.
- Second prize 600 AED.
Video Guide
https://www.youtube.com/watch?v=4BOtr1PZ2D8
