Best AI tools for< Analyze Graphs >

College Tools is an AI-powered homework solver that provides instant, expert help to students. It can answer questions from any website, including those without specialized support, and is fully integrated with Learning Management Systems (LMS) such as McGraw Hill Connect, Blackboard, Canvas, Smartbook, Moodle, and many others. College Tools also offers advanced recognition features that allow users to capture and analyze graphs and image-based questions, and provides detailed step-by-step guidance for each question. The tool is designed to help students improve their understanding and academic results.

The website is an AI tool designed to generate a knowledge graph based on input text. It uses advanced algorithms and machine learning capabilities to streamline operations, deliver personalized experiences, and unlock new possibilities. Users can input text related to various topics, and the tool processes the information to create a structured knowledge graph.

Julius AI is an advanced AI data analyst tool that allows users to analyze data with computational AI, chat with files to get expert-level insights, create sleek data visualizations, perform modeling and predictive forecasting, solve math, physics, and chemistry problems, generate polished analyses and summaries, save time by automating data work, and unlock statistical modeling without complexity. It offers features like generating visualizations, asking data questions, effortless cleaning, instant data export, creating animations, and supercharging data analysis. Julius AI is loved by over 1,200,000 users worldwide and is designed to help knowledge workers make the most out of their data.

ChartAI is an AI-powered tool that helps you create beautiful charts and graphs from your data in seconds. With ChartAI, you can easily create bar charts, line charts, pie charts, and more. You can also customize your charts with different colors, fonts, and styles. ChartAI is the perfect tool for anyone who wants to create professional-looking charts and graphs quickly and easily.

Cognify Insights is an AI-powered research assistant that provides instant understanding of online content such as text, diagrams, tables, and graphs. With a simple drag and drop feature, users can quickly analyze any type of content without leaving their browsing tab. The tool offers valuable insights and helps users unlock information efficiently.

Lychee is an all-in-one data platform designed to streamline the data workflow process, from data collection to analysis, visualization, and sharing. It offers powerful features such as instant graph generation, AI data analysis, website deployment, social media sharing, and team collaboration. Lychee aims to simplify complex data tasks and help users make faster progress in their data-related projects.

ChartFast is an AI Data Analyzer tool that automates data visualization and analysis tasks, powered by GPT-4 technology. It allows users to generate precise and sleek graphs in seconds, process vast amounts of data, and provide interactive data queries and quick exports. With features like specialized internal libraries for complex graph generation, customizable visualization code, and instant data export, ChartFast aims to streamline data work and enhance data analysis efficiency.

Eczemaless is an AI-powered eczema management app that helps users track and manage their condition. The app offers a variety of features, including eczema severity scoring, real-time weather alerts, food tracking, user-friendly graphs, and customized care routines. Eczemaless is available in five languages and has been downloaded over 15,000 times.

Hepta AI is an AI-powered statistics tool designed for scientific research. It simplifies the process of statistical analysis by allowing users to easily input their data and receive comprehensive results, including tables, graphs, and statistical analysis. With a focus on accuracy and efficiency, Hepta AI aims to streamline the research process for scientists and researchers, providing valuable insights and data visualization. The tool offers a user-friendly interface and advanced AI algorithms to deliver precise and reliable statistical outcomes.

VisualizeAI is a powerful AI-powered platform that helps businesses visualize and analyze their data. With VisualizeAI, you can easily create stunning data visualizations, dashboards, and reports that will help you make better decisions. VisualizeAI is perfect for businesses of all sizes, from startups to large enterprises. It is easy to use and affordable, and it can help you save time and money while improving your decision-making.

DevRev is an AI-native modern support platform that offers a comprehensive solution for customer experience enhancement. It provides data engineering, knowledge graph, and customizable LLMs to streamline support, product management, and software development processes. With features like in-browser analytics, consumer-grade social collaboration, and global scale API calls, DevRev aims to bring together different silos within a company to drive efficiency and collaboration. The platform caters to support people, product managers, and developers, automating tasks, assisting in decision-making, and elevating collaboration levels. DevRev is designed to empower digital product teams to assimilate customer feedback in real-time, ultimately powering the next generation of technology companies.

pl.aiwright is an AI-powered dialogue generation tool designed for interactive narratives. It offers features such as analyzing and clustering large dialogue graphs, dialogue generation using a mix of code and natural language, playtests for gathering user feedback, and tools for experimental analysis. The tool enables users to create engaging dialogues for storytelling and gaming purposes.

Wizdom.ai is an AI-powered research intelligence platform that provides comprehensive insights into the global research ecosystem. It continuously monitors billions of data points to generate analytics about scientific developments, helping users make informed decisions and progress research further and faster. Wizdom.ai offers a range of features, including:

Quanty is an AI-driven financial knowledge graph application that provides market insights on crypto and stocks news through advanced algorithms and knowledge graphs. It offers a GraphQL API for deep market understanding, smart data classification, current market insights, entity and relationship extraction, and dynamic GraphQL access. Users can access a wide range of financial news, insights, and analytics seamlessly through Quanty's robust GraphQL API.

xAI Grok is a visual analytics platform that helps users understand and interpret machine learning models. It provides a variety of tools for visualizing and exploring model data, including interactive charts, graphs, and tables. xAI Grok also includes a library of pre-built visualizations that can be used to quickly get started with model analysis.

Electe is an AI-powered platform that empowers businesses to leverage the potential of artificial intelligence for data analysis and insights. With its intuitive interface and advanced AI algorithms, Electe enables users to extract valuable insights from their data, visualize data through intuitive graphs and customizable dashboards, generate personalized notes based on customer order analysis, monitor and compare competitor performance, and automate data extraction and classification using machine learning techniques. The platform also offers features like Q&A Document interaction, advanced presentations generation, daily email reports, and mobile app access. Electe is designed to cater to businesses of all sizes, providing scalable plans with essential functionalities, advanced analysis tools, and premium support.

Deepsheet is a cloud-based spreadsheet application that uses artificial intelligence to help users analyze and visualize data. It offers a variety of features, including the ability to import data from a variety of sources, create charts and graphs, and perform data analysis. Deepsheet is designed to be easy to use, even for users with no prior experience with spreadsheets.

Zelma is an AI-powered research assistant that enables users to find, graph, and understand U.S. school testing data using plain English queries. It allows users to search student test data by school district, demographics, grade, and more, and presents the results with graphs, tables, and descriptions. Zelma aims to make education data accessible and understandable for everyone.

Insight Monk is a deep tech market intelligence platform provided by BIS Research. It offers access to over 1000 deep tech market research reports covering various industries with 5-10 year forecasts. Users can engage in discussions on deep tech markets and trends through the forum, access research documents from reputed organizations, view market statistics, and download graphs and tables for analysis. The platform also offers membership plans for students, academicians, and large teams, with features like expert consultations, access to analyst reports, and personalized research tailored to company needs.

ThirdI is an AI-led digital marketing growth platform that simplifies marketing campaigns, realizes ROI, and saves man hours by generating meaningful insights and impactful recommendations. The platform offers maximum insights with minimal distracting graphs, AI-led recommendations, and instant impact reports for quick actions. ThirdI excels at solving business problems with full-funnel understanding, marketing automation for efficiency, and improved visibility into marketing spend. The platform stands out with features like deep data analysis, simplified marketing campaigns, and enhanced decision-making capabilities.

This repository contains the source code and datasets for Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs accepted to ACL 2024. It proposes a framework called Graph Chain-of-thought (Graph-CoT) to enable Language Models to traverse graphs step-by-step for reasoning, interaction, and execution. The motivation is to alleviate hallucination issues in Language Models by augmenting them with structured knowledge sources represented as graphs.

Awesome-Graph-LLM is a curated collection of research papers exploring the intersection of graph-based techniques with Large Language Models (LLMs). The repository aims to bridge the gap between LLMs and graph structures prevalent in real-world applications by providing a comprehensive list of papers covering various aspects of graph reasoning, node classification, graph classification/regression, knowledge graphs, multimodal models, applications, and tools. It serves as a valuable resource for researchers and practitioners interested in leveraging LLMs for graph-related tasks.

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.

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

WeChatMsg is a tool designed to help users manage and analyze their WeChat data. It aims to provide users with the ability to preserve their precious memories and create a personalized AI companion. The tool allows users to extract and export various types of data from WeChat, such as text, images, contacts, and more. Additionally, it offers features like analyzing chat data and generating visual annual reports. WeChatMsg is built on the idea of empowering users to take control of their data and foster emotional connections through technology.

PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.

Middleware is an open-source engineering management tool that helps engineering leaders measure and analyze team effectiveness using DORA metrics. It integrates with CI/CD tools, automates DORA metric collection and analysis, visualizes key performance indicators, provides customizable reports and dashboards, and integrates with project management platforms. Users can set up Middleware using Docker or manually, generate encryption keys, set up backend and web servers, and access the application to view DORA metrics. The tool calculates DORA metrics using GitHub data, including Deployment Frequency, Lead Time for Changes, Mean Time to Restore, and Change Failure Rate. Middleware aims to provide DORA metrics to users based on their Git data, simplifying the process of tracking software delivery performance and operational efficiency.

Litlyx is a single-line code analytics solution that integrates with every JavaScript/TypeScript framework. It allows you to track 10+ KPIs and custom events for your website or web app. The tool comes with an AI Data Analyst Assistant that can analyze your data, compare data, query metadata, visualize charts, and more. Litlyx is open-source, allowing users to self-host it and create their own version of the dashboard. The tool is user-friendly and supports various JavaScript/TypeScript frameworks, making it versatile for different projects.

AgentNeo is a Python package that provides functionalities for project, trace, dataset, experiment management. It allows users to authenticate, create projects, trace agents and LangGraph graphs, manage datasets, and run experiments with metrics. The tool aims to streamline AI project management and analysis by offering a comprehensive set of features.

This repository is a sample chatbot using the Anthropic company's LLM Claude, one of the foundational models provided by Amazon Bedrock for generative AI. It allows users to have basic conversations with the chatbot, personalize it with their own instructions and external knowledge, and analyze usage for each user/bot on the administrator dashboard. The chatbot supports various languages, including English, Japanese, Korean, Chinese, French, German, and Spanish. Deployment is straightforward and can be done via the command line or by using AWS CDK. The architecture is built on AWS managed services, eliminating the need for infrastructure management and ensuring scalability, reliability, and security.

Obsei is an open-source, low-code, AI powered automation tool that consists of an Observer to collect unstructured data from various sources, an Analyzer to analyze the collected data with various AI tasks, and an Informer to send analyzed data to various destinations. The tool is suitable for scheduled jobs or serverless applications as all Observers can store their state in databases. Obsei is still in alpha stage, so caution is advised when using it in production. The tool can be used for social listening, alerting/notification, automatic customer issue creation, extraction of deeper insights from feedbacks, market research, dataset creation for various AI tasks, and more based on creativity.

This repository evaluates Large Language Models (LLMs) trained on PGN format chess games using linear probes. It assesses the LLMs' internal understanding of board state and their ability to estimate player skill levels. The repo provides tools to train, evaluate, and visualize linear probes on LLMs trained to play chess with PGN strings. Users can visualize the model's predictions, perform interventions on the model's internal board state, and analyze board state and player skill level accuracy across different LLMs. The experiments in the repo can be conducted with less than 1 GB of VRAM, and training probes on the 8 layer model takes about 10 minutes on an RTX 3050. The repo also includes scripts for performing board state interventions and skill interventions, along with useful links to open-source code, models, datasets, and pretrained models.

Quadratic is a modern multiplayer spreadsheet application that integrates Python, AI, and SQL functionalities. It aims to streamline team collaboration and data analysis by enabling users to pull data from various sources and utilize popular data science tools. The application supports building dashboards, creating internal tools, mixing data from different sources, exploring data for insights, visualizing Python workflows, and facilitating collaboration between technical and non-technical team members. Quadratic is built with Rust + WASM + WebGL to ensure seamless performance in the browser, and it offers features like WebGL Grid, local file management, Python and Pandas support, Excel formula support, multiplayer capabilities, charts and graphs, and team support. The tool is currently in Beta with ongoing development for additional features like JS support, SQL database support, and AI auto-complete.

Dify is an open-source LLM app development platform that combines AI workflow, RAG pipeline, agent capabilities, model management, observability features, and more. It allows users to quickly go from prototype to production. Key features include: 1. Workflow: Build and test powerful AI workflows on a visual canvas. 2. Comprehensive model support: Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions. 3. Prompt IDE: Intuitive interface for crafting prompts, comparing model performance, and adding additional features. 4. RAG Pipeline: Extensive RAG capabilities that cover everything from document ingestion to retrieval. 5. Agent capabilities: Define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools. 6. LLMOps: Monitor and analyze application logs and performance over time. 7. Backend-as-a-Service: All of Dify's offerings come with corresponding APIs for easy integration into your own business logic.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

AutoAudit is an open-source large language model specifically designed for the field of network security. It aims to provide powerful natural language processing capabilities for security auditing and network defense, including analyzing malicious code, detecting network attacks, and predicting security vulnerabilities. By coupling AutoAudit with ClamAV, a security scanning platform has been created for practical security audit applications. The tool is intended to assist security professionals with accurate and fast analysis and predictions to combat evolving network threats.

The vscode-dbt-power-user is an open-source extension that enhances the functionality of Visual Studio Code to seamlessly work with dbt™. It provides features such as auto-complete for dbt™ code, previewing query results, column lineage visualization, generating dbt™ models, documentation generation, deferring model builds, running parent/child models and tests with a click, compiled query preview and explanation, project health check, SQL validation, BigQuery cost estimation, and other features like dbt™ logs viewer. The extension is fully compatible with dev containers, code spaces, and remote extensions, supporting dbt™ versions above 1.0.

Expert in Micro Economics, interprets graphs, explains concepts, avoids direct exam answers.

Assists with DGL coding, focusing on edge classification and link prediction.

Fetch and Analyze the Latest News! 📊💡 Get unbiased summaries, detailed bias graphs, and engaging word clouds. Dive into the world of news with a fresh perspective! 🌍📰 Our upgraded News Bias Analyzer GPT is your go-to for insightful analysis of the latest headlines and in-depth articles.

💎 The worlds greatest data analysis tool 💎

Faça perguntas, analise dados e crie gráficos da história dos jogos do clássico BRAPEL (Grêmio Esportivo Brasil e Esporte Clube Pelotas)

Indian stock market analysis with TradingView data and breakout graphs.

Ask: "What graphs can you create from MY pee times data file (.xlsx)?" Show to your Urologist.

Propagation Analysis over Graphs

Your Stata research assistant

Your go-to guide for STATA

Expert in Stata for statistical analysis guidance

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Japanese patent data graph generator with user engagement

I specialize in making decompiled code clearer and easier to understand.

Get instant math solutions by uploading an image with Math expression.

Leading AI in graphene research, offering innovative insights and solutions, powered by OpenAI.

Analyze and reverse engineer images. Receive style descriptions and image re-creation prompts.

As a Good Design Advisor, I provide consultation and advice on design topics and analyze designs that are provided through documents or links. I can also generate visual representations myself to illustrate design concepts.

Analyze the uploaded image and creates a 3D Cartoon Image and prompt

Helps beginners understand DirectX 12 concepts and terminology