Best AI tools for< Create Visualizations >

Luminal is a powerful AI copilot that enables users to clean, transform, and analyze spreadsheets 10x faster. It offers fast and efficient data analysis capabilities, allowing users to perform editing operations, answer complex questions, and run AI-enabled operations using natural language. Luminal simplifies data processing tasks, saving users time and effort. The application supports multiple languages, ensures secure data hosting with encryption, and offers flexible pricing plans to cater to different user needs.

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.

Lumina is a research tool that uses artificial intelligence to help researchers find and analyze information more quickly and easily. It can be used to search for articles, books, and other resources, and it can also be used to analyze data and create visualizations. Lumina is designed to make research more efficient and productive.

Sonify is a company that specializes in the intersection of audio, data, and emerging technologies. They design and develop audio-first products and data-driven solutions. Sonify's mission is to make data more accessible and understandable through the use of sound. They believe that sound is a powerful tool that can be used to communicate complex information in a way that is both engaging and informative.

Amazon Q in QuickSight is a generative BI assistant that makes it easy to build and consume insights. With Amazon Q, BI users can build, discover, and share actionable insights and narratives in seconds using intuitive natural language experiences. Analysts can quickly build visuals and calculations and refine visuals using natural language. Business users can self-serve data and insights using natural language. Amazon Q is built with security and privacy in mind. It can understand and respect your existing governance identities, roles, and permissions and use this information to personalize its interactions. If a user doesn't have permission to access certain data without Amazon Q, they can't access it using Amazon Q either. Amazon Q in QuickSight is designed to meet the most stringent enterprise requirements from day one—none of your data or Amazon Q inputs and outputs are used to improve underlying models of Amazon Q for anyone but you.

Quadratic is an infinite spreadsheet with Python, SQL, and AI. It combines the familiarity of a spreadsheet with the power of code, allowing users to analyze data, write code, and create visualizations in a single environment. With built-in Python library support, users can bring open source tools directly to their spreadsheets. Quadratic also features real-time collaboration, allowing multiple users to work on the same spreadsheet simultaneously. Additionally, Quadratic is built for speed and performance, utilizing Web Assembly and WebGL to deliver a smooth and responsive experience.

Athena Intelligence is an AI-native analytics platform and artificial employee designed to accelerate analytics workflows by offering enterprise teams co-pilot and auto-pilot modes. Athena learns your workflow as a co-pilot, allowing you to hand over controls to her for autonomous execution with confidence. With Athena, everyone in your enterprise has access to a data analyst, and she doesn't take days off. Simple integration to your Enterprise Data Warehouse Chat with Athena to query data, generate visualizations, analyze enterprise data and codify workflows. Athena's AI learns from existing documentation, data and analyses, allowing teams to focus on creating new insights. Athena as a platform can be used collaboratively with co-workers or Athena, with over 100 users in the same report or whiteboard environment concurrently making edits. From simple queries and visualizations to complex industry specific workflows, Athena enables you with SQL and Python-based execution environments.

Coursera is an online learning platform that offers courses, specializations, and degrees from top universities and companies. It provides a wide range of subjects, including business, computer science, data science, and more. Coursera also offers a variety of learning formats, including self-paced courses, live online classes, and guided projects. With Coursera, you can learn at your own pace and on your own schedule.

Vizly is an AI-powered data analysis tool that empowers users to make the most of their data. It allows users to chat with their data, visualize insights, and perform complex analysis. Vizly supports various file formats like CSV, Excel, and JSON, making it versatile for different data sources. The tool is free to use for up to 10 messages per month and offers a student discount of 50%. Vizly is suitable for individuals, students, academics, and organizations looking to gain actionable insights from their data.

Looker is a business intelligence platform that offers embedded analytics and AI-powered BI solutions. Leveraging Google's AI-led innovation, Looker delivers intelligent BI by combining foundational AI, cloud-first infrastructure, industry-leading APIs, and a flexible semantic layer. It allows users to build custom data experiences, transform data into integrated experiences, and create deeply integrated dashboards. Looker also provides a universal semantic modeling layer for unified, trusted data sources and offers self-service analytics capabilities through Looker and Looker Studio. Additionally, Looker features Gemini, an AI-powered analytics assistant that accelerates analytical workflows and offers a collaborative and conversational user experience.

PandasAI is an open-source AI tool designed for conversational data analysis. It allows users to ask questions in natural language to their enterprise data and receive real-time data insights. The tool is integrated with various data sources and offers enhanced analytics, actionable insights, detailed reports, and visual data representation. PandasAI aims to democratize data analysis for better decision-making, offering enterprise solutions for stable and scalable internal data analysis. Users can also fine-tune models, ingest universal data, structure data automatically, augment datasets, extract data from websites, and forecast trends using AI.

ML Clever is a no-code machine learning platform that empowers users to build powerful ML models with one click, explore what-if scenarios to guide decisions, and create interactive dashboards to explain results. It combines automated machine learning, interactive dashboards, and flexible prediction tools in one platform, allowing users to transform data into business insights without the need for data scientists or coding skills.

OAD is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With OAD, users can easily import data from various sources, clean and preprocess data, perform statistical analysis, and create customizable visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, OAD can help you streamline your data analysis workflow and uncover valuable insights from your data.

big-AGI is an AI suite designed for professionals seeking function, form, simplicity, and speed. It offers best-in-class Chats, Beams, and Calls with AI personas, visualizations, coding, drawing, side-by-side chatting, and more, all wrapped in a polished UX. The tool is powered by the latest models from 12 vendors and open-source servers, providing users with advanced AI capabilities and a seamless user experience. With continuous updates and enhancements, big-AGI aims to stay ahead of the curve in the AI landscape, catering to the needs of both developers and AI enthusiasts.

The Data Scientist Roadmap2024 provides a comprehensive guide to mastering essential tools for data science success. It includes programming languages, machine learning libraries, cloud platforms, and concepts categorized by difficulty. The roadmap covers a wide range of topics from programming languages to machine learning techniques, data visualization tools, and DevOps/MLOps tools. It also includes web development frameworks and specific concepts like supervised and unsupervised learning, NLP, deep learning, reinforcement learning, and statistics. Additionally, it delves into DevOps tools like Airflow and MLFlow, data visualization tools like Tableau and Matplotlib, and other topics such as ETL processes, optimization algorithms, and financial modeling.

AI Gallery is a showcase site built using React and Nextjs for static site generation, featuring interactive visualizations of classic algorithms, classic games implementation, and various interesting widgets. The project utilizes AI assistance from Claude 3.5 and GPT-4 to create components and enhance the development process. It aims to continually add more components with AI assistance, providing a platform for contributors to leverage AI in frontend development.

AI-Driven Research Assistant is an advanced AI-powered system utilizing specialized agents for data analysis, visualization, and report generation. It integrates LangChain, OpenAI's GPT models, and LangGraph for complex research processes. Key features include hypothesis generation, data processing, web search, code generation, and report writing. The system's unique Note Taker agent maintains project state, reducing overhead and improving context retention. System requirements include Python 3.10+ and Jupyter Notebook environment. Installation involves cloning the repository, setting up a Conda virtual environment, installing dependencies, and configuring environment variables. Usage instructions include setting data, running Jupyter Notebook, customizing research tasks, and viewing results. Main components include agents for hypothesis generation, process supervision, visualization, code writing, search, report writing, quality review, and note-taking. Workflow involves hypothesis generation, processing, quality review, and revision. Customization is possible by modifying agent creation and workflow definition. Current issues include OpenAI errors, NoteTaker efficiency, runtime optimization, and refiner improvement. Contributions via pull requests are welcome under the MIT License.

Data Formulator is an AI-powered tool developed by Microsoft Research to help data analysts create rich visualizations iteratively. It combines user interface interactions with natural language inputs to simplify the process of describing chart designs while delegating data transformation to AI. Users can utilize features like blended UI and NL inputs, data threads for history navigation, and code inspection to create impressive visualizations. The tool supports local installation for customization and Codespaces for quick setup. Developers can build new data analysis tools on top of Data Formulator, and research papers are available for further reading.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

GPT-Vis is a tool designed for GPTs, generative AI, and LLM projects. It provides components such as LLM Protocol for conversational interaction, LLM Component for application development, and LLM access for knowledge base and model solutions. The tool aims to facilitate rapid integration into AI applications by offering a visual protocol, built-in components, and chart recommendations for LLM.

Scira is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for data exploration, cleaning, and modeling. With Scira, users can easily import datasets, perform statistical analysis, create insightful visualizations, and generate reports. The tool supports various data formats and offers a wide range of statistical functions and visualization options. Whether you are a data scientist, researcher, or student, Scira can help you uncover valuable insights from your data and communicate your findings effectively.

Cookiecutter Data Science (CCDS) is a tool for setting up a data science project template that incorporates best practices. It provides a logical, reasonably standardized but flexible project structure for doing and sharing data science work. The tool helps users to easily start new data science projects with a well-organized directory structure, including folders for data, models, notebooks, reports, and more. By following the project template created by CCDS, users can streamline their data science workflow and ensure consistency across projects.

Marimo is a reactive Python notebook that ensures code and outputs consistency by automatically running dependent cells or marking them as stale. It replaces various tools like Jupyter, streamlit, and more, offering an interactive environment with features like binding UI elements to Python, reproducibility, executability as scripts or apps, shareability, and designed for data tasks. It is git-friendly, offers a modern editor with AI assistants, and comes with built-in package management. Marimo provides deterministic execution order, dynamic markdown and SQL capabilities, and a performant runtime. It is easy to get started with and suitable for both beginners and power users.

Fueling-Ambitions-Via-Book-Discoveries is an Advanced Machine Learning & AI Course designed for students, professionals, and AI researchers. The course integrates rigorous theoretical foundations with practical coding exercises, ensuring learners develop a deep understanding of AI algorithms and their applications in finance, healthcare, robotics, NLP, cybersecurity, and more. Inspired by MIT, Stanford, and Harvard’s AI programs, it combines academic research rigor with industry-standard practices used by AI engineers at companies like Google, OpenAI, Facebook AI, DeepMind, and Tesla. Learners can learn 50+ AI techniques from top Machine Learning & Deep Learning books, code from scratch with real-world datasets, projects, and case studies, and focus on ML Engineering & AI Deployment using Django & Streamlit. The course also offers industry-relevant projects to build a strong AI portfolio.

This public repository contains API, tools, and packages for Datagrok, a web-based data analytics platform. It offers support for scientific domains, applications, connectors to web services, visualizations, file importing, scientific methods in R, Python, or Julia, file metadata extractors, custom predictive models, platform enhancements, and more. The open-source packages are free to use, with restrictions on server computational capacities for the public environment. Academic institutions can use Datagrok for research and education, benefiting from reproducible and scalable computations and data augmentation capabilities. Developers can contribute by creating visualizations, scientific methods, file editors, connectors to web services, and more.

Context7 is a powerful tool for analyzing and visualizing data in various formats. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With advanced features such as data filtering, aggregation, and customization, Context7 is suitable for both beginners and experienced data analysts. The tool supports a wide range of data sources and formats, making it versatile for different use cases. Whether you are working on exploratory data analysis, data visualization, or data storytelling, Context7 can help you uncover valuable insights and communicate your findings effectively.

MarvinsAIRA is the original classic (1.x) Marvin's Awesome iRacing App, which is no longer being updated. For the latest version, users can refer to MAIRA Refactored (2.x) repository at the provided link.

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