摘要
在大数据环境下,处理庞大的数据集与实现复杂的机器学习算法愈发关键。为解决这一挑战,分布式机器学习框架应运而生。通过分布式计算资源的协同工作,可以提高机器学习模型的训练效率和性能。
In the big data environment,processing large datasets and implementing complex machine learning algorithms have become increasingly crucial.To address this challenge,distributed machine learning frameworks have emerged,which improve the training efficiency and performance of machine learning models through the collaborative work of distributed computing resources.
作者
马威
李振亚
MA Wei;LI Zhenya(The 28th Research Institute,China Electronics Technology Group Corporation,Nanjing 210007,China)
出处
《计算机应用文摘》
2024年第12期108-110,共3页
Chinese Journal of Computer Application
