Oct 14, 2021 · In this paper, we introduce a simple yet efficient framework, MLife, for fast and effective initialization of the major stages of ML lifecycle.
Driven by real-world experience in building and maintaining ML systems, we find that it is more efficient to initialize the major stages of ML lifecycle first ...
For this, we introduce a simple yet flexible framework, MLife, for fast ML lifecycle initialization. This is built on the fact that data flow in MLife is in a ...
The objective of the present study is to develop a Customized Automated Machine Learning (CAML) framework to support machine learning models in manufacturing ...
For this, we introduce a simple yet flexible framework, MLife, for fast ML lifecycle initialization. This is built on the fact that data flow in MLife is in a ...
Oct 14, 2021 · For this, we introduce a simple yet flexible framework, MLife, for fast ML lifecycle initialization. This is built on the fact that data flow in ...
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MLife: a lite framework for machine learning lifecycle initialization. Cong Yang; Wenfeng Wang; John See. OriginalPaper 14 October 2021 Pages: 2993 - 3013. RB ...
May 25, 2021 · MLife: a lite framework for machine learning lifecycle initialization. Abstract. Machine learning (ML) lifecycle is a cyclic process to build ...
MLife: a lite framework for machine learning lifecycle initialization · Cong Yang, Wenfeng Wang, Yunhui Zhang, Zhikai Zhang, Lina Shen, Yipeng Li, John See.