A deep learning process intelligent assembly method based on semantic web
A technology of deep learning and assembly method, which is applied in the direction of integrated learning to achieve the effect of easy assembly and realization
Active Publication Date: 2022-07-08
FUZHOU UNIV
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However, the heterogeneity of machine learning algorithm frameworks, the diversity of machine learning process assembly, and the complexity of software and hardware resource management have brought great challenges to the construction of machine learning infrastructure.
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[0033] The present invention will be further described below with reference to the accompanying drawings and embodiments.
[0034] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
[0035] It should be noted that the terminology used herein is for the purpose of describing specific embodiments only, and is not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural as well, furthermore, it is to be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates that There are features, steps, operations, devices, components and / ...
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The present invention proposes an intelligent assembly method of deep learning process based on semantic web, which includes the following steps; Step S1: select several preprocessing methods for image data from preprocessing methods supported by different frameworks, and use automatic or manual preprocessing methods for image data. Step S2: Select the network structure from the model structures supported by different frameworks, in an automatic or manual way; Step S3: Select the optimizer to be used in the training process from the optimizers supported by different frameworks to automatically or manually Manual method; Step S4: establish a semantic model to describe the functions of each algorithm module of the different frameworks selected in the above three steps, assemble, build a machine learning model training process, perform model training and result evaluation; intelligent assembly and training evaluation of the process The process can be repeated, and the model with the best effect is reserved as the final model; the present invention can effectively perform intelligent assembly and automatic exploration for the process of deep learning in machine learning.
Description
technical field [0001] The invention relates to the technical field of machine learning and deep learning, in particular to a deep learning process intelligent assembly method based on semantic web. Background technique [0002] Machine learning infrastructure is the core prerequisite for the widespread application and efficient integration of big data in various industries. However, the heterogeneity of machine learning algorithm framework, the diversity of machine learning process assembly, and the complexity of software and hardware resource management have all brought great challenges to the construction of machine learning infrastructure. SUMMARY OF THE INVENTION [0003] The present invention proposes a deep learning process intelligent assembly method based on semantic web, which can effectively carry out intelligent assembly and automatic exploration for the deep learning process in machine learning. [0004] The present invention adopts the following technical so...
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IPC IPC(8): G06N20/20
CPCG06N20/20
Inventor 郭文忠柯逍陈柏涛
Owner FUZHOU UNIV