Hello and welcome to the hackathon! This is a beginner friendly event with focus on exploring key machine learning concepts. However, we also welcome more experienced participants to join. More experienced participants will have the opportunity to go beyond the basics covered in our teaching sessions. We will not hold you back when it comes to model complexity, data pre-processing and feature engineering. If you don't know what all these terms mean, don't worry we will explain everything in the teaching sessions.
This hackathon will span over 2 weeks. On Saturday February 12th, we will hold 2 teaching sessions on explorative data analysis and supervised learning. We will also release the competition dataset and a sample solution on that day. Participants then have 2 weeks to make a submission. About 1 week prior to the submission deadline we will host an online drop in session where you can ask for feedback. Throughout the 2 weeks you will always have the opportunity to ask for help on the hackathon teams channel.
Spotted a mistake, dead link, or have suggestions for improvements? Message us using the links below.
- Make sure you have registered on the Google form. Otherwise, you will not be invited/accepted to the Microsoft Teams group.
- Join the Week 5 ML Hackathon Teams Group and turn on notifications to stay up to date.
All other relevant details should be available on this page. If you have any questions feel free to reach out by using the contact links below. Viel Spass!
The event will take place in S0.11. Please make sure to show up on time. After the dataset release you will have 2 weeks to make a submission. On February 22nd we will also host an online drop-in session on Teams where you can ask us for feedback before you make a submission.
Again, the dataset will be published on February 12th.
| Date | Time | Event |
|---|---|---|
| 12th Feb | 3-4pm | Introduction to Machine Learning |
| 12th Feb | 4-5pm | Sample notebook presentation |
| 12th Feb | 5-6pm | In person guidance |
| 12th Feb | 6pm | Free pizza |
| 22nd Feb | 6pm | Online drop-in session |
| 26th Feb | 6pm | Submission deadline |
Predict the box office revenue based on the movie features of the IMDB dataset. Make sure to include an EDA before your modelling section.
- Sample ML notebook
- Sample Pandas and Matplot lib notebook to be used for the EDA part of the ML notebook
Please send a copy of your notebook to hackathon@wdss.io.
We will judge your submission based on the quality of the notebook as well as how well your regression model performs.
The winner/winning team will receive a shoutout on our social media accounts (including LinkedIn if you wish so). We will also link to your solution from this GitHub page.
This is up to you to decide. If you would like to be part of a team, please contact Valentin Kodderitzsch on MS teams. We will try to our best to allocate teams of up to 4 people based on each participant's skill level. We will also be discussing teams during the Hackathon introduction workshop which will be held on February 12th 2022 at 3pm in S0.11.
No problem. Simply email hackathon@wdss.io and explain the situation.
We will provide help throughout the hackathon in a number of ways:
- Most help will be provided during the workshop on February 12th
- After the workshop you will find help by messaging the 'Get Help' channel on Teams
- We will also host an online drop-in session on February 22nd
This hackathon was written and is primarily managed by Valentin Kodderitzsch. If you need to contact me please reach out on Microsoft Teams or message me on LinkedIn.