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Data-Centric AI Competition | From Model-centric to Data-centric AI | Andrew NG urges data-centric
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Data-Centric AI Competition | From Model-centric to Data-centric AI | Andrew NG urges data-centric
A collaboration between DeepLearning.AI and Landing AI, the Data-Centric AI Competition aims to elevate data-centric approaches to improving the performance of machine learning models.
In most machine learning competitions, you are asked to build a high-performance model given a fixed dataset. However, machine learning has matured to the point that high-performance model architectures are widely available, while approaches to engineering datasets have lagged. The Data-Centric AI Competition inverts the traditional format and instead asks you to improve a dataset given a fixed model. We will provide you with a dataset to improve by applying data-centric techniques such as fixing incorrect labels, adding examples that represent edge cases, apply data augmentation, etc.
Contestants must submit their altered dataset for evaluation by September 4, 2021. 6PM PT (We picked this date because it is the birthday of John McCarthy, who had coined the term artificial intelligence!) The top three winners from each of the two categories (Best Performance Overall and Most Innovative) will be invited to a private event with Andrew Ng to share ideas about how to grow the data-centric movement and will be highlighted in The Batch and other DeepLearning.AI and Landing AI channels.
A machine learning competition that wants to break the traditional codes. This challenge was proposed by landing AI and Deep learning.AI to reverse the traditional format of ML where the participants are asked to create the high-performance model from a fixed dataset. Participants need to improve the dataset based on the model already proposed. A dataset will be provided to developers and they will have to enrich it by applying data-centric techniques.
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