Andrew Ng Urges ML Community To Be More Data-Centric

Andrew Ng Urges ML Community To Be More Data-Centric

Andrew Ng drew the ML community’s attention towards MLOps, a field dealing with building and deploying ML models more systematically.

58 mentions: @AndrewYNg@maria_axente@JackRaifer@mattlungrenMD@Analyticsindiam@fraukolos@ohhrosie@ThisIsBernardo
Date: 2021/04/06 10:30

Referring Tweets

@JackRaifer We all want to jump into building #Machinearning models, but data is much more important. We need to spend more time curating it, managing it and understanding it. #DataScience #66DaysOfData t.co/ReROrDxpOV
@AndrewYNg Nice writeup by @Analyticsindiam on why I think we should move from model-centric AI development (where the emphasis is on improving models) toward #DataCentricAI (where we systematically improve the data, using MLOps tools). t.co/7ClnrLKVGC
@maria_axente This is really a no brainier but it has to be stressed out - @AndrewYNg wants the ML community to focus more on data than models; he emphasized the importance of MLOps to build and deploy machine learning models more systematically. t.co/D1Eo9tfcGZ t.co/UeFIqhflRL
@ohhrosie “If 80% of our work is data preparation, then ensuring data quality is the important work of a machine learning team.” SIIIMMMM t.co/486skoLy4f
@jimitjim How to accelerate building and deploying AI systems? By moving from model-centric AI development toward data-centric one, says Andrew Ng. t.co/RT0eQ9ecQ5 #itjim #AI #DataScience #machinelearning #MLops
@mavendi1 “If 80 percent of our work is data preparation, then ensuring data quality is the important work of a machine learning team.” Andrew Ng #ML #AI #DS #ArtificialIntelligence t.co/G4Seg4XtwV
@ThisIsBernardo "The most important task of MLOps is to make high-quality data available. Labelling consistency is key. Data quality on a basic model is better than chasing the state-of-the-art models with low-quality data." Andrew Ng by @Analyticsindiam t.co/I82gU6C88x t.co/KSrvK1bW4c

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