Problem solving with “AI Challenger global AI contest”

Problem solving with “AI Challenger global AI contest”Experience from participating in computer vision competition hosted by Chinese data science platform AI ChallengerIlya BoytsovBlockedUnblockFollowFollowingDec 31, 2018In this article I will share my experience solving a video classification problem in a Chinese machine learning competition.There are a lot of data science platforms for competitors..We used to think about Kaggle – the most popular one..Anyway, there is a number of other platforms that provide data scientists with challenging tasks, and it is a good time to explore them..This is why me and my teammate Alexey Grigorev entered Short video real-time classification competition at Chinese platform AI Challenger..Big thanks to kaggle grandmaster Artur Kuzin who became our mentor in this competition..He was helping us with creative ideas and provided us with a GPU server.Competition descriptionThe dataset of videos was about 2 TB large and was split into train and validation sets..There were 2 test sets: test A and test B..The videos could have from 1 to 3 labels each so it was a multi-label classification..For example below is a frame from a video that has 2 classes: piano and babyAnd here is a full list of possible tags:This competition had a complex metric for evaluation..Besides accuracy time restriction was added as an evaluation metric..You may think of it as the overall time taken from inputting a single video to outputting a single prediction.Finally taking into account these 2 formulas the composite metric was calculated as the weighted distance between submitted results and the reference point..You may read more about that metric here.The key idea is that organizers wanted from data science community a high-speed application that could be used in industry.. More details

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