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基于字符级卷积神经网络的细粒度的中文情感分析以及具体的应用,将顾客打分和评论情感进行两极映射,使用数据自动标注和基于弱监督预训练的数据增强方式自动扩充和优化数据集,实验证实了在情感分类中,使用本文的字符级卷积神经网络(C-CNN-SA)可以在不依赖分词的情况下,达到的精度和 F 值均高于词级粒度。并将模型上线使用,利用tensoflow+flask restful做出的后端服务化,具体的项目细节和讲解看右面的ppt
Dispatch 305 is a website to present a broker service for trucks. This repo contains the backend api developed usign Flask and Flask RESTX as an extension of Flask RESTPlus
Salary Prediction API using Flask predicts salaries for freshers joining organizations based on factors like past experience, company switches, courses completed, and academic marks. This Flask-based API allows users to input their details and receive a salary prediction. With no user interface, it's designed for integration into other applications
Backend workflows for SatVision's real-time satellite image and land cover segmentation renderer. Deploys the novel patchify-process-reconstruct approach to run DL-driven segmentation inference in real-time.