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Jinhua Wang's Projects

cnsenti icon cnsenti

中文情感分析库(Chinese Sentiment))可对文本进行情绪分析、正负情感分析。

conv_arithmetic icon conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

covid-19 icon covid-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

customer_satisfaction_analysis icon customer_satisfaction_analysis

基于在线民宿 UGC 数据的意见挖掘项目,包含数据挖掘和NLP 相关的处理,负责数据采集、主题抽取、情感分析等任务。目的是克服用户打分和评论不一致,实时对在线民宿的满意度评测,包含在线评论采集和情感可视化分析。搭建了百度地图POI查询入口,可以进行自动化的批量查询 POI 信息的功能;构建了基于在线民宿语料的 LDA 自动主题聚类模型,利用主题中心词能找出对应的主题属性字典;以用户打分作为标注,然后 litNlp 自带的字符级 TextCNN 进行情感分析,将情感分类概率分布作为情感趋势,最后通过 POI 热力图的方式对不同地域的民宿满意度进行展示。软件版本请见链接。

cyclegan icon cyclegan

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

deepiv icon deepiv

Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction

deepscenetextreader icon deepscenetextreader

This is a c++ project deploying a deep scene text reading pipeline with tensorflow. It reads text from natural scene images. It uses frozen tensorflow graphs. The detector detect scene text locations. The recognizer reads word from each detected bounding box.

discovery icon discovery

A very simple library to discover and retrieve data from nearby devices (even if the peer app works at background).

dmtcp icon dmtcp

DMTCP: Distributed MultiThreaded CheckPointing

dnode icon dnode

turtles all the way down rpc

dowhy icon dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

dropbox-uploader icon dropbox-uploader

Dropbox Uploader is a BASH script which can be used to upload, download, list or delete files from Dropbox, an online file sharing, synchronization and backup service.

easierlife icon easierlife

Coding makes my life easier. This is a factory contains many little programs.

econml icon econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

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