Contests in Signal Processing and Machine Learning

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10 years of news and resources for members of the IEEE Signal Processing Society

Contests in Signal Processing and Machine Learning

Recent years have seen a rapid increase in the number of machine learning and signal processing contests. Some of those currently open include: From Kaggle hosted contests, Google is inviting the Kaggle community to join efforts to accelerate research in large-scale video understanding, while giving participants access to the Google Cloud Machine Learning Engine. In this competition, participants are challenged to develop classification algorithms which accurately assign video-level labels using the new and improved YT-8M V2 dataset. The dataset was created from over 7 million YouTube videos (450,000 hours of video) and includes video labels from a vocabulary of 4716 classes (3.4 labels/video on average). From the domain of Signal Processing in Remote Sensing, Planet and its Brazilian partner SCCON are challenging Kagglers to label satellite image chips with atmospheric conditions and various classes of land cover/land use. Resulting algorithms will help the global community better understand where, how, and why deforestation happens all over the world - and ultimately how to respond. Another contest also from Kaggle focuses on home value prediction. Zillow Prize, a competition with a one million dollar grand prize, is challenging the data science community to help push the accuracy of the Zestimate home value estimator even further. Winning algorithms stand to impact the home values of 110M homes across the U.S. In this competition, participants will develop an algorithm that makes predictions about the future sale prices of homes. The contest is structured into two rounds, the qualifying round which opens May 24, 2017 and the private round for the 100 top qualifying teams that opens on Feb 1st, 2018.

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