Best AI tools for< Recommendation Systems >
20 - AI tool Sites
NVIDIA
NVIDIA is a world leader in artificial intelligence computing. The company's products and services are used by businesses and governments around the world to develop and deploy AI applications. NVIDIA's AI platform includes hardware, software, and tools that make it easy to build and train AI models. The company also offers a range of cloud-based AI services that make it easy to deploy and manage AI applications. NVIDIA's AI platform is used in a wide variety of industries, including healthcare, manufacturing, retail, and transportation. The company's AI technology is helping to improve the efficiency and accuracy of a wide range of tasks, from medical diagnosis to product design.
Tech Xplore
Tech Xplore is a leading source of science and technology news, covering the latest breakthroughs in research and innovation across a wide range of disciplines, including artificial intelligence, robotics, computer science, and more. The website provides in-depth articles, interviews with experts, and up-to-date information on the latest developments in the field of AI and its applications.
Amazon Science
Amazon Science is a research and development organization within Amazon that focuses on developing new technologies and products in the fields of artificial intelligence, machine learning, and computer science. The organization is home to a team of world-renowned scientists and engineers who are working on a wide range of projects, including developing new algorithms for machine learning, building new computer vision systems, and creating new natural language processing tools. Amazon Science is also responsible for developing new products and services that use these technologies, such as the Amazon Echo and the Amazon Fire TV.
Big Vision
Big Vision provides consulting services in AI, computer vision, and deep learning. They help businesses build specific AI-driven solutions, create intelligent processes, and establish best practices to reduce human effort and enable faster decision-making. Their enterprise-grade solutions are currently serving millions of requests every month, especially in critical production environments.
Shaped
Shaped is an AI tool designed to provide relevant recommendations and search results to increase engagement, conversion, and revenue. It offers a configurable system that adapts in real-time, with features such as easy set-up, real-time adaptability, state-of-the-art model library, high customizability, and explainable results. Shaped is suitable for technical teams and offers white-glove support. It specializes in real-time ranking systems and supports multi-modal unstructured data understanding. The tool ensures secure infrastructure and has advantages like increased redemption rate, average order value, and diversity.
ICD AI
ICD AI is an advanced artificial intelligence tool designed to assist healthcare professionals in accurately assigning diagnostic codes to patient records. The tool utilizes machine learning algorithms to analyze medical data and suggest appropriate ICD codes, streamlining the coding process and reducing errors. With its user-friendly interface and robust features, ICD AI is revolutionizing medical coding practices and improving efficiency in healthcare facilities.
JobsRemote.ai
JobsRemote.ai is a free artificial intelligence-based platform that offers a curated selection of remote job-friendly tools to enhance the remote work experience. Users can browse thousands of handpicked tools suitable for remote jobs, ensuring high-quality recommendations without ads, scams, or junk listings. The platform focuses on providing legitimate and suitable job listings from top companies worldwide, streamlining the application process for job seekers. With a user-friendly interface and personalized recommendations, JobsRemote.ai aims to connect remote professionals with quality remote job opportunities efficiently.
Linkter
Linkter is the #1 AI internal linking tool designed for SEO superstars. It automates the process of building strategic internal links, saving SEOs hundreds of hours of manual work. With advanced features like an AI recommendation system, anchor text manager, and custom AI implementation, Linkter enhances SEO rankings, indexation, and user experience. The tool revolutionizes website optimization by streamlining internal linking tasks and improving overall website visibility and performance.
Critique
Critique is an AI tool that redefines browsing by offering autonomous fact-checking, informed question answering, and a localized universal recommendation system. It automatically critiques comments and posts on platforms like Reddit, Youtube, and Linkedin by vetting text on any website. The tool cross-references and analyzes articles in real-time, providing vetted and summarized information directly in the user's browser.
Balik Games
Balik Games is a dynamic company specializing in developing innovative games and apps that cater to various interests and needs. With a focus on quality, diversity, and user experience, Balik Games is committed to creating fun, engaging, and easy-to-use products that deliver maximum value to customers. Their app offers a unique combination of ASMR soundscapes and a personalized recommendation system powered by AI, providing a customized experience tailored to individual preferences. Two of their popular games include Blocks!, a puzzle game challenging problem-solving skills, and Swipe Kingdom, a card-based game where players take on the role of a Viking King.
Swipe Insight
Swipe Insight is a mobile application that provides users with daily updates on digital marketing and analytics trends, news, and strategies. The app features a personalized feed that adapts to the user's preferences, intelligent insights that distill complex topics into concise summaries, and a curated selection of content from over 100 trusted sources. Swipe Insight is designed to help users stay ahead in the industry with just minutes of reading per day.
Shaped
Shaped is a cloud-based platform that provides APIs and tools for building and deploying ranking systems. It offers a variety of features to help developers quickly and easily create and manage ranking models, including a multi-connector SQL interface, a real-time feature store, and a library of pre-built models. Shaped is designed to be scalable, cost-efficient, and easy to use, making it a great option for businesses of all sizes.
Gift Recommender
Gift Recommender is an AI-powered application designed to assist users in finding the perfect gift for their loved ones. By providing basic information about the recipient such as name, age, gender, price range, and interests, the AI generates personalized gift recommendations. The system learns from user feedback to continuously improve its suggestions. While the AI provides recommendations, it acknowledges that the best gift is often something personal and encourages users to provide feedback for better training.
Strategic Intelligence
Strategic Intelligence is an AI-powered platform that helps businesses make better decisions by providing them with real-time insights into their data. The platform uses a variety of machine learning and artificial intelligence techniques to analyze data from a variety of sources, including social media, news articles, and financial reports. This data is then used to generate reports and insights that can help businesses identify opportunities, mitigate risks, and make better decisions.
ColdIQ
ColdIQ is an AI-powered sales prospecting tool that helps B2B companies with revenue above $100k/month to build outbound systems that sell for them. The tool offers end-to-end cold outreach campaign setup and management, email infrastructure setup and warmup, audience research and targeting, data scraping and enrichment, campaigns optimization, sending automation, sales systems implementation, training on tools best practices, sales tools recommendations, free gap analysis, sales consulting, and copywriting frameworks. ColdIQ leverages AI to tailor messaging to each prospect, automate outreach, and flood calendars with opportunities.
Wasps
Wasps is an AI code review tool that integrates seamlessly into VSCode, providing developers with a fast and efficient way to understand their codebase, detect and fix code issues using AI and Gitsecure. With Wasps, developers can identify and fix buggy & vulnerable code in minutes, receive clear and actionable feedback driven by deep analysis, and get recommendations for potential issues and improvements within their codebase. The tool allows developers to keep coding as usual while Wasps analyzes their code for them, making it easier to maintain code quality and keep bugs out of their code.
Quickchat AI
Quickchat AI is a custom AI assistant designed to automate customer support, lead generation, and more. It allows users to design, tweak, and deploy their own AI assistant trained on their data. Quickchat AI offers a range of features including customizable AI assistant name, conversation style, knowledge and actions, and deployment options. It also provides integrations with popular tools and systems, making it easy to use AI in everyday workflows.
Yonder
Yonder is an AI-powered chatbot and review platform designed specifically for the tourism industry. It helps tourism businesses to increase website sales, generate more enquiries, and save staff time by providing AI chatbot services, personalized recommendations, live reviews showcase, website chat support, customer surveys, team feedback categorization, and online review management. Yonder's AI chatbot can answer up to 80% of customer questions immediately on the website and Messenger, 24/7. The platform also offers features like conversation analytics, ratings breakdown, and integration with reservation systems for automation and efficiency.
MiMi
MiMi is a website intelligence tool that uses AI to enhance the user experience and drive sales. It offers a range of features including semantic search, chatbot, recommendations, virtual assistant, dynamic pricing, and automation. MiMi's AI engine can automatically learn and update knowledge from your site to provide an AI chatbot that can answer questions from visitors automatically. The machine learning algorithms can also learn from your site products and visitor behavior to bring recommender systems for your site. MiMi's AI algorithm serves as a virtual sales assistant, assisting websites in making flexible and tailored pricing decisions for each customer based on their behavior.
5-Out
5-Out is an AI Restaurant Forecasting Software designed to boost profit for restaurants. It utilizes machine learning, artificial intelligence, and predictive analysis to automate smarter decisions. The application integrates various systems like Point of Sale, labor scheduling, purchasing, inventory, weather, social media, and more to predict sales and optimize labor and purchasing. With real-time insights and recommendations, 5-Out helps restaurants make data-driven decisions to increase profitability.
20 - Open Source AI Tools
Recommendation-Systems-without-Explicit-ID-Features-A-Literature-Review
This repository is a collection of papers and resources related to recommendation systems, focusing on foundation models, transferable recommender systems, large language models, and multimodal recommender systems. It explores questions such as the necessity of ID embeddings, the shift from matching to generating paradigms, and the future of multimodal recommender systems. The papers cover various aspects of recommendation systems, including pretraining, user representation, dataset benchmarks, and evaluation methods. The repository aims to provide insights and advancements in the field of recommendation systems through literature reviews, surveys, and empirical studies.
Next-Generation-LLM-based-Recommender-Systems-Survey
The Next-Generation LLM-based Recommender Systems Survey is a comprehensive overview of the latest advancements in recommender systems leveraging Large Language Models (LLMs). The survey covers various paradigms, approaches, and applications of LLMs in recommendation tasks, including generative and non-generative models, multimodal recommendations, personalized explanations, and industrial deployment. It discusses the comparison with existing surveys, different paradigms, and specific works in the field. The survey also addresses challenges and future directions in the domain of LLM-based recommender systems.
recommenders
Recommenders is a project under the Linux Foundation of AI and Data that assists researchers, developers, and enthusiasts in prototyping, experimenting with, and bringing to production a range of classic and state-of-the-art recommendation systems. The repository contains examples and best practices for building recommendation systems, provided as Jupyter notebooks. It covers tasks such as preparing data, building models using various recommendation algorithms, evaluating algorithms, tuning hyperparameters, and operationalizing models in a production environment on Azure. The project provides utilities to support common tasks like loading datasets, evaluating model outputs, and splitting training/test data. It includes implementations of state-of-the-art algorithms for self-study and customization in applications.
LLMRec
LLMRec is a PyTorch implementation for the WSDM 2024 paper 'Large Language Models with Graph Augmentation for Recommendation'. It is a novel framework that enhances recommenders by applying LLM-based graph augmentation strategies to recommendation systems. The tool aims to make the most of content within online platforms to augment interaction graphs by reinforcing u-i interactive edges, enhancing item node attributes, and conducting user node profiling from a natural language perspective.
Deej-AI
Deej-A.I. is an advanced machine learning project that aims to revolutionize music recommendation systems by using artificial intelligence to analyze and recommend songs based on their content and characteristics. The project involves scraping playlists from Spotify, creating embeddings of songs, training neural networks to analyze spectrograms, and generating recommendations based on similarities in music features. Deej-A.I. offers a unique approach to music curation, focusing on the 'what' rather than the 'how' of DJing, and providing users with personalized and creative music suggestions.
redis-ai-resources
A curated repository of code recipes, demos, and resources for basic and advanced Redis use cases in the AI ecosystem. It includes demos for ArxivChatGuru, Redis VSS, Vertex AI & Redis, Agentic RAG, ArXiv Search, and Product Search. Recipes cover topics like Getting started with RAG, Semantic Cache, Advanced RAG, and Recommendation systems. The repository also provides integrations/tools like RedisVL, AWS Bedrock, LangChain Python, LangChain JS, LlamaIndex, Semantic Kernel, RelevanceAI, and DocArray. Additional content includes blog posts, talks, reviews, and documentation related to Vector Similarity Search, AI-Powered Document Search, Vector Databases, Real-Time Product Recommendations, and more. Benchmarks compare Redis against other Vector Databases and ANN benchmarks. Documentation includes QuickStart guides, official literature for Vector Similarity Search, Redis-py client library docs, Redis Stack documentation, and Redis client list.
kdbai-samples
KDB.AI is a time-based vector database that allows developers to build scalable, reliable, and real-time applications by providing advanced search, recommendation, and personalization for Generative AI applications. It supports multiple index types, distance metrics, top-N and metadata filtered retrieval, as well as Python and REST interfaces. The repository contains samples demonstrating various use-cases such as temporal similarity search, document search, image search, recommendation systems, sentiment analysis, and more. KDB.AI integrates with platforms like ChatGPT, Langchain, and LlamaIndex. The setup steps require Unix terminal, Python 3.8+, and pip installed. Users can install necessary Python packages and run Jupyter notebooks to interact with the samples.
NineRec
NineRec is a benchmark dataset suite for evaluating transferable recommendation models. It provides datasets for pre-training and transfer learning in recommender systems, focusing on multimodal and foundation model tasks. The dataset includes user-item interactions, item texts in multiple languages, item URLs, and raw images. Researchers can use NineRec to develop more effective and efficient methods for pre-training recommendation models beyond end-to-end training. The dataset is accompanied by code for dataset preparation, training, and testing in PyTorch environment.
VectorETL
VectorETL is a lightweight ETL framework designed to assist Data & AI engineers in processing data for AI applications quickly. It streamlines the conversion of diverse data sources into vector embeddings and storage in various vector databases. The framework supports multiple data sources, embedding models, and vector database targets, simplifying the creation and management of vector search systems for semantic search, recommendation systems, and other vector-based operations.
Awesome-LLM4Graph-Papers
A collection of papers and resources about Large Language Models (LLM) for Graph Learning (Graph). Integrating LLMs with graph learning techniques to enhance performance in graph learning tasks. Categorizes approaches based on four primary paradigms and nine secondary-level categories. Valuable for research or practice in self-supervised learning for recommendation systems.
ai_projects
This repository contains a collection of AI projects covering various areas of machine learning. Each project is accompanied by detailed articles on the associated blog sciblog. Projects range from introductory topics like Convolutional Neural Networks and Transfer Learning to advanced topics like Fraud Detection and Recommendation Systems. The repository also includes tutorials on data generation, distributed training, natural language processing, and time series forecasting. Additionally, it features visualization projects such as football match visualization using Datashader.
Awesome-LLM4RS-Papers
This paper list is about Large Language Model-enhanced Recommender System. It also contains some related works. Keywords: recommendation system, large language models
Paper-Reading-ConvAI
Paper-Reading-ConvAI is a repository that contains a list of papers, datasets, and resources related to Conversational AI, mainly encompassing dialogue systems and natural language generation. This repository is constantly updating.
superlinked
Superlinked is a compute framework for information retrieval and feature engineering systems, focusing on converting complex data into vector embeddings for RAG, Search, RecSys, and Analytics stack integration. It enables custom model performance in machine learning with pre-trained model convenience. The tool allows users to build multimodal vectors, define weights at query time, and avoid postprocessing & rerank requirements. Users can explore the computational model through simple scripts and python notebooks, with a future release planned for production usage with built-in data infra and vector database integrations.
Cool-GenAI-Fashion-Papers
Cool-GenAI-Fashion-Papers is a curated list of resources related to GenAI-Fashion, including papers, workshops, companies, and products. It covers a wide range of topics such as fashion design synthesis, outfit recommendation, fashion knowledge extraction, trend analysis, and more. The repository provides valuable insights and resources for researchers, industry professionals, and enthusiasts interested in the intersection of AI and fashion.
interpret
InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...
thecodersgig
TheCodersGig is an AI-powered open-source social network platform for developers, facilitating seamless connection and collaboration. It features an integrated utility marketplace for creating plugins easily, automating backend development with scalable code. The user-friendly interface supports API integration, data models, databases, authentication, and authorization. The platform's architecture includes frontend, backend, AI services, database, marketplace, security, and DevOps layers, enabling customization and diverse integrations. Key components encompass technologies like React.js, Node.js, Python-based AI frameworks, SQL/NoSQL databases, payment gateways, security protocols, and DevOps tools for automation and scalability.
vectordb-recipes
This repository contains examples, applications, starter code, & tutorials to help you kickstart your GenAI projects. * These are built using LanceDB, a free, open-source, serverless vectorDB that **requires no setup**. * It **integrates into python data ecosystem** so you can simply start using these in your existing data pipelines in pandas, arrow, pydantic etc. * LanceDB has **native Typescript SDK** using which you can **run vector search** in serverless functions! This repository is divided into 3 sections: - Examples - Get right into the code with minimal introduction, aimed at getting you from an idea to PoC within minutes! - Applications - Ready to use Python and web apps using applied LLMs, VectorDB and GenAI tools - Tutorials - A curated list of tutorials, blogs, Colabs and courses to get you started with GenAI in greater depth.
chromem-go
chromem-go is an embeddable vector database for Go with a Chroma-like interface and zero third-party dependencies. It enables retrieval augmented generation (RAG) and similar embeddings-based features in Go apps without the need for a separate database. The focus is on simplicity and performance for common use cases, allowing querying of documents with minimal memory allocations. The project is in beta and may introduce breaking changes before v1.0.0.
20 - OpenAI Gpts
TB Order Recommendation System
Given a set of Parameters, Provides a set of Order Recommendations
Stream Scout
A movie and TV show , Songs & Books recommendation assistant for various streaming platforms.
O cara do som
Expert in residential speaker systems, offering detailed advice and product recommendations.
Europe Ethos Guide for AI
Ethics-focused GPT builder assistant based on European AI guidelines, recommendations and regulations
직업 추천 요정, 담비 (휴먼디자인 성향분석 직업추천) human design
나에게 맞는 직업과 진로 추천받기. 적성에 맞는 진로 상담, 직업추천, 휴먼디자인, Based on Human Design System
JudgeSchlegelGPT
Focused solely on tech in the legal system. No unrelated advice or recommendations.
Awesome-Selfhosted
Recommends self-hosted IT solutions, tailored for professionals (from https://awesome-selfhosted.net/)
Letter of Recommendation Expert
A counselor aiding in writing recommendation letters for PhD applications, with a formal and informative tone.
Green Card Recommendation Letter Expert
Expert in drafting recommendation letters for U.S. green card application under EB-1A and EB2-NIW applications. Please start from the conversation starters but with the info of yourself.
IDA Pro Plugins recommendation expert.
Ask me to recommend a plugin or script from the official Hex-Rays plugin repository
Ecommerce App Recommendation GPT
Finds the best Shopify app for your requirements and budget