两周时间后,在三个典型场景下,Data-centric策略都在模型关键指标上取得显著进步。 搭建模型的误区 Andrew认为,在搭建模型时,特征生产与模型训练的时间占比应该是8:2,然而目前大部分AI研究的文章(>99%),均发力于模型探索方面。 人们很容易认为模型效果不好,是因为模型不好,却忽略了数据集本身对模型效果的巨大影响。
Last week,Andrew Ngdrew the ML community’s attention towardsMLOps, a field dealing with building and deploying machine learning models more systematically. Andrew Ng explained how machine learning development could accelerate if more emphasis is on being data-centric than model-centric....
and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, ...
and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, ...