#新手入门#A free, open source, self-hosted customer feedback tool 🦊
翻译 - 免费，开源，自托管的客户反馈工具🦊
#新手入门#Track your customers feedback to build better products with LogChimp. ⭐️ Star to support our work!
Multi Class Text (Feedback) Classification using CNN, GRU Network and pre trained Word2Vec embedding, word embeddings on TensorFlow.
Using Machine Learning to Analyze & Visualize Consumer Behavior
A customer feedback demo application for collecting reviews for a product after a successful purchase.
B2B Customer Feedback collection and analysis SaaS using AI/ML to generate, cluster and rank actionable tasks, helping you to grow your business.
#博客#🏠 The source code of bimbala.com.
#面试#A short hand-picked collection of resources to help SaaS founders get started with customer interviews.
Customer Feedback and Sentiment Analysis
Developed a full-stack web application for catering services using the MERN stack (MongoDB, Express.js, React, Node.js). Features include menu management, order tracking, customer feedback, payment ga...
#自然语言处理#💬 It uses NLP techniques to classify reviews as positive, neutral or negative, providing valuable insights into customer feedback.
The cab booking project is used to book online from where you need there are three user admin and user and cab driver, The admin can check the cab details who all booked who all login etc, I have prov...
#计算机科学#This project analyzes customer feedback for skincare products by predicting sentiment using an unsupervised model. It includes a web application for real-time sentiment analysis, an ETL pipeline built...
A Rust crate for calculating Net Promoter Score (NPS) from survey responses.
#搜索#Mechanism for a search engine backed by inverted indexes (from using Lucene and Hadoop). Word embeddings and Snippet generation were used.
Emaily is a full-stack web application to collect customer feedback. It is for startups and product managers. It is written in JavaScript using Node.js, Express, Mongo DB, React, Redux, and Material U...
#自然语言处理#An Analysis of the tech review and customer feedback on twitter, provided an insight into what the customers seek from Apple’s iPhone Series.