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Steven Tan's Projects

115 icon 115

Assistant for 115 to export download links to aria2-rpc

115sha1link icon 115sha1link

生成本地文件115转存链接以便在未安装客户端情况下离线秒传

amazon-fine-food-reviews-analysis icon amazon-fine-food-reviews-analysis

This is a supervised learning problem where we need to predict sentiments of reviews each review with a reviewer’s score indicating the sentiment of the reviewer. Our task is to predict a reviewer’s score on a scale of 1 to 5, where 1 indicates the reviewer extremely dislikes the food he or she mentions in the review and 5 indicates the user likes the food a lot.The goal will be to maximize the accuracy of this classification. 

amazon-products-sentiment-analysis icon amazon-products-sentiment-analysis

Sentiment analysis is the interpretation and classification of emotions (positive, negative and neutral) within text data using text analysis techniques. Sentiment analysis allows businesses to identify customer sentiment toward products, brands or services in online conversations and feedback. Sentiment analysis is a text analysis method that detects polarity (e.g. a positive or negative opinion) within text, whether a whole document, paragraph, sentence, or clause. Why Perform Sentiment Analysis? It’s estimated that 80% of the world’s data is unstructured, in other words it’s unorganized. Huge volumes of text data (emails, support tickets, chats, social media conversations, surveys, articles, documents, etc), is created every day but it’s hard to analyze, understand, and sort through, not to mention time-consuming and expensive. Sentiment analysis, however, helps businesses make sense of all this unstructured text by automatically tagging it. Benefits of sentiment analysis include: Sorting Data at Scale Can you imagine manually sorting through thousands of tweets, customer support conversations, or surveys? There’s just too much data to process manually. Sentiment analysis helps businesses process huge amounts of data in an efficient and cost-effective way. Real-Time Analysis Sentiment analysis can identify critical issues in real-time, for example is a PR crisis on social media escalating? Is an angry customer about to churn? Sentiment analysis models can help you immediately identify these kinds of situations and gauge brand sentiment, so you can take action right away. Consistent criteria It’s estimated that people only agree around 60-65% of the time when determining the sentiment of a particular text. Tagging text by sentiment is highly subjective, influenced by personal experiences, thoughts, and beliefs. By using a centralized sentiment analysis system, companies can apply the same criteria to all of their data, helping them improve accuracy and gain better insights.

amazon_spider_sys icon amazon_spider_sys

Amazon Spider 亚马逊商品信息抓取系统,包含商品监控模块,商品评价监控模块,商品库存监控系统,评论词云模块,用户管理模块

av_data_capture_fixbug icon av_data_capture_fixbug

本地电影刮削与整理一体化解决方案,修复了原工程大量的bug,例如无法区分番号相同影片、封面图获取错误等等

cookiecutter-flask-restful icon cookiecutter-flask-restful

Flask cookiecutter template for builing APIs with flask-restful, including JWT auth, cli, tests, swagger, docker and more

discuzapi icon discuzapi

Discuz的python API,可以登陆、签到、发帖、回帖、上传图片等。python直接import就可以用,你们也感受一下!

fis icon fis

Front-end Integrated Solution - 前端集成解决方案

fks icon fks

前端技能汇总 Frontend Knowledge Structure

nlp-sentimentanalysis_amazonreviews icon nlp-sentimentanalysis_amazonreviews

The best businesses understand the sentiment of their customers — what people are saying, how they’re saying it, and what they mean. Amazon is one of the pioneer companies who gave significant importance to user sentiments. It all started with “Dell Hell” case of laptop manufacturing company Dell. Customer sentiment can be found in tweets, comments, reviews, or other places where people mention your brand. Sentiment Analysis is the domain of understanding these emotions with software, and it’s a must-understand for developers and business leaders in a modern workplace. The aim of this project to detect sentiments of the Amazon users.

pythoncrawler icon pythoncrawler

This repository is some small projects for DannyWu learning python crawlers.Welcome your visit and hope to learn together!

qv2ray icon qv2ray

:star: Linux / Windows / macOS 跨平台 V2Ray 客户端 | 支持 VMess / VLESS / SSR / Trojan / Trojan-Go / NaiveProxy / HTTP / HTTPS / SOCKS5 | 使用 C++ / Qt 开发 | 可拓展插件式设计 :star:

ruoyi-vue-pro icon ruoyi-vue-pro

🔥 官方推荐 🔥 RuoYi-Vue 全新 Pro 版本,优化重构所有功能。基于 Spring Boot + MyBatis Plus + Vue & Element 实现的后台管理系统 + 微信小程序,支持 RBAC 动态权限、数据权限、SaaS 多租户、Flowable 工作流、三方登录、支付、短信、商城、CRM、ERP 等功能。你的 ⭐️ Star ⭐️,是作者生发的动力!

socket.io icon socket.io

Realtime application framework for Node.JS, with HTML5 WebSockets and cross-browser fallbacks support.

vue-element-ui-admin icon vue-element-ui-admin

:maple_leaf: 一个基于 Vue Element UI 的后台模板,做了目录结构的整理和常用方法的封装,开箱即用 :)

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