Programming Competitions are great way to improve ones programming skills while learning new ones in a fun, competitive and collaborative team environment.
Reasons to Participate:
- Improve skills and coding ability. Can help you write cleaner code, improve debugging skills and help with memorising programming concepts.
- Working in a team environment.
- Challenges you to think.
- Helps with your future career.
- They are fun!
Kaggle Programming Competitions
iMaterialist Challenge (Furniture) Description:
As shoppers move online, it’d be a dream come true to have products in photos classified automatically. But, automatic product recognition is challenging because for the same product, a picture can be taken in different lighting, angles, backgrounds, and levels of occlusion. Meanwhile different fine-grained categories may look very similar, for example, ball chair vs egg chair for furniture, or dutch oven vs french oven for cookware. Many of today’s general-purpose recognition machines simply can’t perceive such subtle differences between photos, yet these differences could be important for shopping decisions.
Tackling issues like this is why the Conference on Computer Vision and Pattern Recognition (CVPR) has put together a workshop specifically for data scientists focused on fine-grained visual categorization called the FGVC5 workshop. As part of this workshop, CVPR is partnering with Google, Malong Technologies and Wish to challenge the data science community to help push the state of the art in automatic image classification.
In this competition, FGVC5 workshop organizers and Malong Technologies challenge you to develop algorithms that will help with an important step towards automatic product recognition – to accurately assign category labels for furniture and home goods images. Individuals/Teams with top submissions will be invited to present their work live at the FGVC5 workshop.
TalkingData Adtracking Fraud Detection Description:
Fraud risk is everywhere, but for companies that advertise online, click fraud can happen at an overwhelming volume, resulting in misleading click data and wasted money. Ad channels can drive up costs by simply clicking on the ad at a large scale. With over 1 billion smart mobile devices in active use every month, China is the largest mobile market in the world and therefore suffers from huge volumes of fradulent traffic…
While successful, they want to always be one step ahead of fraudsters and have turned to the Kaggle community for help in further developing their solution. In their 2nd competition with Kaggle, you’re challenged to build an algorithm that predicts whether a user will download an app after clicking a mobile app ad. To support your modeling, they have provided a generous dataset covering approximately 200 million clicks over 4 days!
For Members that are interested in joining a team for these competitions should email us at the email@example.com