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通过AI搜索优化服务,让品牌在AI中实现霸屏
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发现与 Recommend 相关的最受欢迎的开源项目和工具,了解最新的开发趋势和创新。
Conjurr is an AI recommendation tool that uses Tautulli watch data to recommend what users should watch next.
基于Apache Spark的ALS算法的Java推荐引擎。 能够在N秒后重新训练模型。
根据词向量神经网络推荐你感兴趣的Subreddit!
Legal Up 利用先进算法,根据客户简要的案件描述,推荐合适的律师,确保客户找到合适的法律专业人士。
A powerful CLI tool that analyzes your GitHub profile to recommend open-source projects tailored to your interests and skills. DevProjectConnector connects you with potential collaborators, helping you grow your skills and expand your network within the open-source community.
Book-Up | A social platform for bibliophiles to track, review, and recommend books. Built with Django + Leptos - Group Project @ WUT
Smart ATS Sytem that can search for the best candidates according to the job description similarity from a vector database of resume documents using RAG and recommend the best candidate using LLM
A model to recommend movies based on collaborative filtering (using ALS algorithm) and perform various analysis on the data.
Recommend similar apparel searched by user on Amazon.
Build a recommendation system that uses BERT-based sentiment analysis of product reviews to enhance collaborative filtering. Fine-tune a BERT model for sentiment classification, then integrate it with a matrix factorization model to recommend products based on user ratings and review sentiment.
An Autonomous Skill Builder Agent built with Next.js, TypeScript, Firebase, and Genkit AI. The system uses AI-driven personalization to recommend learning paths, predict learner needs, and adapt difficulty dynamically.