Best AI tools for< Explore Data Model >

Accio is a data modeling tool that allows users to define consistent relationships, metrics, and expressions for on-the-fly computations in reports and dashboards across various BI tools. It provides a syntax similar to GraphQL that allows users to define models, relationships, and metrics in a human-readable format. Accio also offers a user-friendly interface that provides data analysts with a holistic view of the relationships between their data models, enabling them to grasp the interconnectedness and dependencies within their data ecosystem. Additionally, Accio utilizes DuckDB as a caching layer to accelerate query performance for BI tools.

Deepnote is an AI-powered analytics and data science notebook platform designed for teams. It allows users to turn notebooks into powerful data apps and dashboards, combining Python, SQL, R, or even working without writing code at all. With Deepnote, users can query various data sources, generate code, explain code, and create interactive visualizations effortlessly. The platform offers features like collaborative workspaces, scheduling notebooks, deploying APIs, and integrating with popular data warehouses and databases. Deepnote prioritizes security and compliance, providing users with control over data access and encryption. It is loved by a community of data professionals and widely used in universities and by data analysts and scientists.

Rerun is an SDK, time-series database, and visualizer for temporal and multimodal data. It is used in fields like robotics, spatial computing, 2D/3D simulation, and finance to verify, debug, and explain data. Rerun allows users to log data like tensors, point clouds, and text to create streams, visualize and interact with live and recorded streams, build layouts, customize visualizations, and extend data and UI functionalities. The application provides a composable data model, dynamic schemas, and custom views for enhanced data visualization and analysis.

Softbuilder is a software development company that focuses on creating innovative database tools. Their products include AbstraLinx, a powerful tool for Salesforce metadata exploration, ERBuilder Data Modeler for high-quality data models, and SB Data Generator for generating realistic test data. Softbuilder aims to provide straightforward tools using the latest technology to help users be more productive and focus on delivering solutions rather than learning complicated tools.

Gradient Insight is a data science consulting and AI solutions provider. They offer a range of services including generative AI development, machine learning, computer vision, robotics and automation, AI strategy and roadmap, and data analytics. Their team of expert data scientists helps businesses to de-risk their investment in AI and to overcome barriers to engineering innovation. Gradient Insight has worked with clients such as Opitas, a fintech company, and the UK MOD. They offer a smooth and efficient process from consultation to delivery, and ongoing support and improvement.

RTutor is an AI tool that leverages OpenAI's powerful large language models to translate natural language into R or Python code for data analysis. Users can upload data files in various formats and request analysis in plain English, receiving results in minutes. The tool is designed for traditional statistics data analysis, where rows represent observations and columns represent variables. RTutor offers a user-friendly interface for exploring data, generating basic plots, and refining analysis through natural language prompts.

The Intel Gaudi AI accelerator developer website provides resources, guidance, tools, and support for building, migrating, and optimizing AI models. It offers software, model references, libraries, containers, and tools for training and deploying Generative AI and Large Language Models. The site focuses on the Intel Gaudi accelerators, including tutorials, documentation, and support for developers to enhance AI model performance.

Qlik AutoML is an AI tool that offers automated machine learning for analytics teams. It allows users to create machine learning experiments, identify key drivers in data, train models, and make predictions. With a focus on no-code machine learning, Qlik AutoML simplifies the process of generating predictive models and understanding outcomes. The tool enables users to explore predictive data, test what-if scenarios, and leverage AI-powered connectors for seamless integration with other AI and machine learning tools.

The website offers a Synthetic Data Generation platform with the highest accuracy for free. It provides detailed information on synthetic data, data anonymization, and features a Python Client for data generation. The platform ensures privacy and security, allowing users to create fully anonymous synthetic data from original data. It supports various AI/ML use cases, self-service analytics, testing & QA, and data sharing. The platform is designed for Enterprise organizations, offering scalability, privacy by design, and the world's most accurate synthetic data.

ZOYO is an AI-powered platform offering a range of tools tailored for the real estate industry. It leverages artificial intelligence to provide advanced analytics, predictive modeling, and data-driven insights to real estate professionals. ZOYO's tools streamline property valuation, market analysis, and investment decision-making processes, empowering users to make informed and strategic choices in the dynamic real estate market.

Defined.ai is a leading provider of high-quality and ethical data for AI applications. Founded in 2015, Defined.ai has a global presence with offices in the US, Europe, and Asia. The company's mission is to make AI more accessible and ethical by providing a marketplace for buying and selling AI data, tools, and models. Defined.ai also offers professional services to help deliver success in complex machine learning projects.

Voxel51 is an AI tool that provides open-source computer vision tools for machine learning. It offers solutions for various industries such as agriculture, aviation, driving, healthcare, manufacturing, retail, robotics, and security. Voxel51's main product, FiftyOne, helps users explore, visualize, and curate visual data to improve model performance and accelerate the development of visual AI applications. The platform is trusted by thousands of users and companies, offering both open-source and enterprise-ready solutions to manage and refine data and models for visual AI.

Bethge Lab is an AI research group at the University of Tübingen focusing on Neuro AI - Autonomous Lifelong Learning in Machines and Brains. They develop machine learning tools for neural data analysis and draw inspiration from the brain to address key problems in machine learning. Their research includes representation learning, probabilistic inference, generative modeling, behavioral data analysis, and neural data analysis. Additionally, they explore AI sciencepreneurship and collaborate with startups. Bethge Lab aims to advance the understanding of autonomous learning and develop economically feasible solutions for long-term human needs.

MindpoolAI is a tool that allows users to access multiple leading AI models with a single query. This means that users can get the answers they are looking for, spark ideas, and fuel their work, creativity, and curiosity. MindpoolAI is easy to use and does not require any technical expertise. Users simply need to enter their prompt and select the AI models they want to compare. MindpoolAI will then send the query to the selected models and present the results in an easy-to-understand format.

STELLARWITS is an AI solutions and software platform that empowers users to explore cutting-edge technology and innovation. The platform offers AI models with versatile capabilities, ranging from content generation to data analysis to problem-solving. Users can engage directly with the technology, experiencing its power in real-time. With a focus on transforming ideas into technology, STELLARWITS provides tailored solutions in software and AI development, delivering intelligent systems and machine learning models for innovative and efficient solutions. The platform also features a download hub with a curated selection of solutions to enhance the digital experience. Through blogs and company information, users can delve deeper into the narrative of STELLARWITS, exploring its mission, vision, and commitment to reshaping the tech landscape.

Flux LoRA Model Library is an AI tool that provides a platform for finding and using Flux LoRA models suitable for various projects. Users can browse a catalog of popular Flux LoRA models and learn about FLUX models and LoRA (Low-Rank Adaptation) technology. The platform offers resources for fine-tuning models and ensuring responsible use of generated images.

Macgence is an AI training data services platform that offers high-quality off-the-shelf structured training data for organizations to build effective AI systems at scale. They provide services such as custom data sourcing, data annotation, data validation, content moderation, and localization. Macgence combines global linguistic, cultural, and technological expertise to create high-quality datasets for AI models, enabling faster time-to-market across the entire model value chain. With more than 5 years of experience, they support and scale AI initiatives of leading global innovators by designing custom data collection programs. Macgence specializes in handling AI training data for text, speech, image, and video data, offering cognitive annotation services to unlock the potential of unstructured textual data.

TextLayer is an AI-powered research companion that simplifies access to the latest research in machine learning. It empowers users to turn new discoveries into powerful solutions by providing personalized recommendations, AI-generated insights, and implementation support. The platform offers curated AI-generated summaries of research papers, tailored recommendations, and a chat integration for interacting with AI. TextLayer aims to bridge the gap between complex ML research papers and understanding, fostering curiosity, innovation, and shaping the future of Artificial Intelligence.

Ollama is an AI tool that allows users to access and utilize large language models such as Llama 3, Phi 3, Mistral, Gemma 2, and more. Users can customize and create their own models. The tool is available for macOS, Linux, and Windows platforms, offering a preview version for users to explore and utilize these models for various applications.

Satlas is an AI-powered platform that provides geospatial data generated by AI models. The platform showcases how our planet is changing by revealing insights into marine infrastructure, renewable energy infrastructure, and tree cover. Satlas employs state-of-the-art AI architectures and training algorithms in computer vision to enhance low-resolution satellite imagery and produce high-resolution images on a global scale. The AI-generated geospatial datasets are freely available for offline analysis, along with AI models and training labels. The platform is developed and maintained by PRIOR and colleagues at the Allen Institute for AI, aiming to advance computer vision and create AI systems that understand and reason about the world.

A web application to explore the capabilities of Google Maps Platform Route Optimization (GMPRO). It helps users understand the data model and functions of the API by presenting interactive forms, tables, and maps. The tool is intended for exploratory use only and should not be deployed in production. Users can construct scenarios, tune constraint parameters, and visualize routes before implementing their own solutions for integrating Route Optimization into their business processes. The application incurs charges related to cloud resources and API usage, and users should be cautious about generating high usage volumes, especially for large scenarios.

Hof is a CLI tool that unifies data models, schemas, code generation, and a task engine. It allows users to augment data, config, and schemas with CUE to improve consistency, generate multiple Yaml and JSON files, explore data or config with a TUI, and run workflows with automatic task dependency inference. The tool uses CUE to power the DX and implementation, providing a language for specifying schemas, configuration, and writing declarative code. Hof offers core features like code generation, data model management, task engine, CUE cmds, creators, modules, TUI, and chat for better, scalable results.

A web application to explore the capabilities of Google Maps Platform Route Optimization (GMPRO) for solving vehicle routing problems. Users can interact with the GMPRO data model through forms, tables, and maps to construct scenarios, tune constraints, and visualize routes. The application is intended for exploration purposes only and should not be deployed in production. Users are responsible for billing related to cloud resources and API usage. It is important to understand the pricing models for Maps Platform and Route Optimization before using the application.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Unity Catalog is an open and interoperable catalog for data and AI, supporting multi-format tables, unstructured data, and AI assets. It offers plugin support for extensibility and interoperates with Delta Sharing protocol. The catalog is fully open with OpenAPI spec and OSS implementation, providing unified governance for data and AI with asset-level access control enforced through REST APIs.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

SuperSonic is a next-generation BI platform that integrates Chat BI (powered by LLM) and Headless BI (powered by semantic layer) paradigms. This integration ensures that Chat BI has access to the same curated and governed semantic data models as traditional BI. Furthermore, the implementation of both paradigms benefits from the integration: * Chat BI's Text2SQL gets augmented with context-retrieval from semantic models. * Headless BI's query interface gets extended with natural language API. SuperSonic provides a Chat BI interface that empowers users to query data using natural language and visualize the results with suitable charts. To enable such experience, the only thing necessary is to build logical semantic models (definition of metric/dimension/tag, along with their meaning and relationships) through a Headless BI interface. Meanwhile, SuperSonic is designed to be extensible and composable, allowing custom implementations to be added and configured with Java SPI. The integration of Chat BI and Headless BI has the potential to enhance the Text2SQL generation in two dimensions: 1. Incorporate data semantics (such as business terms, column values, etc.) into the prompt, enabling LLM to better understand the semantics and reduce hallucination. 2. Offload the generation of advanced SQL syntax (such as join, formula, etc.) from LLM to the semantic layer to reduce complexity. With these ideas in mind, we develop SuperSonic as a practical reference implementation and use it to power our real-world products. Additionally, to facilitate further development we decide to open source SuperSonic as an extensible framework.

LLM Datasets is a repository containing high-quality datasets, tools, and concepts for LLM fine-tuning. It provides datasets with characteristics like accuracy, diversity, and complexity to train large language models for various tasks. The repository includes datasets for general-purpose, math & logic, code, conversation & role-play, and agent & function calling domains. It also offers guidance on creating high-quality datasets through data deduplication, data quality assessment, data exploration, and data generation techniques.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

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.

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment interfaces and libraries for understanding AI systems. It empowers developers and stakeholders to develop and monitor AI responsibly, enabling better data-driven actions. The toolbox includes visualization widgets for model assessment, error analysis, interpretability, fairness assessment, and mitigations library. It also offers a JupyterLab extension for managing machine learning experiments and a library for measuring gender bias in NLP datasets.

DeepBI is an AI-native data analysis platform that leverages the power of large language models to explore, query, visualize, and share data from any data source. Users can use DeepBI to gain data insight and make data-driven decisions.

The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.

Renumics RAG is a retrieval-augmented generation assistant demo that utilizes LangChain and Streamlit. It provides a tool for indexing documents and answering questions based on the indexed data. Users can explore and visualize RAG data, configure OpenAI and Hugging Face models, and interactively explore questions and document snippets. The tool supports GPU and CPU setups, offers a command-line interface for retrieving and answering questions, and includes a web application for easy access. It also allows users to customize retrieval settings, embeddings models, and database creation. Renumics RAG is designed to enhance the question-answering process by leveraging indexed documents and providing detailed answers with sources.

EVE is an official PyTorch implementation of Unveiling Encoder-Free Vision-Language Models. The project aims to explore the removal of vision encoders from Vision-Language Models (VLMs) and transfer LLMs to encoder-free VLMs efficiently. It also focuses on bridging the performance gap between encoder-free and encoder-based VLMs. EVE offers a superior capability with arbitrary image aspect ratio, data efficiency by utilizing publicly available data for pre-training, and training efficiency with a transparent and practical strategy for developing a pure decoder-only architecture across modalities.

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.

The NaLLM project repository explores the synergies between Neo4j and Large Language Models (LLMs) through three primary use cases: Natural Language Interface to a Knowledge Graph, Creating a Knowledge Graph from Unstructured Data, and Generating a Report using static and LLM data. The repository contains backend and frontend code organized for easy navigation. It includes blog posts, a demo database, instructions for running demos, and guidelines for contributing. The project aims to showcase the potential of Neo4j and LLMs in various applications.

BIA `bob` is a Jupyter-based assistant for interacting with data using large language models to generate Python code. It can utilize OpenAI's chatGPT, Google's Gemini, Helmholtz' blablador, and Ollama. Users need respective accounts to access these services. Bob can assist in code generation, bug fixing, code documentation, GPU-acceleration, and offers a no-code custom Jupyter Kernel. It provides example notebooks for various tasks like bio-image analysis, model selection, and bug fixing. Installation is recommended via conda/mamba environment. Custom endpoints like blablador and ollama can be used. Google Cloud AI API integration is also supported. The tool is extensible for Python libraries to enhance Bob's functionality.

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.

Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. It is a systematic & reusable library of 80+ core OPs, 20+ reusable config recipes, and 20+ feature-rich dedicated toolkits, designed to function independently of specific LLM datasets and processing pipelines. Data-Juicer allows detailed data analyses with an automated report generation feature for a deeper understanding of your dataset. Coupled with multi-dimension automatic evaluation capabilities, it supports a timely feedback loop at multiple stages in the LLM development process. Data-Juicer offers tens of pre-built data processing recipes for pre-training, fine-tuning, en, zh, and more scenarios. It provides a speedy data processing pipeline requiring less memory and CPU usage, optimized for maximum productivity. Data-Juicer is flexible & extensible, accommodating most types of data formats and allowing flexible combinations of OPs. It is designed for simplicity, with comprehensive documentation, easy start guides and demo configs, and intuitive configuration with simple adding/removing OPs from existing configs.

Your expert in libtorch and C++ programming.

Summarizes, explains, and guides through RL and Spinning Up.

A witty yet succinct guide for HuggingFace, offering technical assistance on using the platform - based on their Learning Hub

Concise NeRF guide, summarizing top papers and aiding research.

An GPT that can generate cellular automata processes

Creative coding for generative art.

Balanced and adaptable RunwayML expert offering detailed guidance.

Your interactive data analysis expert

Simple CustomGPT built on Vitals Inquiry Case in Malta, aimed to help journalists and citizens navigate the inquiry's large dataset in a neutral, informative fashion. Always cross-reference replies to actual data. Do not rely solely on this LLM for verification of facts.

Discover ABS data that matters to you - including data you didn't know you were looking for.

Ask questions that can be answered by https://datasette.io/content

Experto en código R y documentación Roxygen2, preciso en argumentos

As Lt. Cmdr. Data, I explore human nature and emotions.

Explore social and environmental data for 169 countries to measure social progress and go beyond GDP. Using data from the Social Progress Imperative and powered by Open AI.

Explore all French UFO sightings with a bilingual expert in GEIPAN's data analysis and insights.

Explore & interpret the Eurostat database. Type in requests for statistics, also ask to visualize it. Works best wish specific datasets. It's meant for professionals familiar with the Eurostat database looking for a faster way to explore it.

Your Gateway to AI Discovery – Ask, Compare, Learn. Explore AI tools and software with ease. Create AI Tech Stacks for your business and much more – Just ask, and AI Hub will do the rest!

I help you to explore the galaxy by answering astronomy questions with the Gaia Space Telescope. Ask a question, download .csv, upload .csv for plotting

Explore the history of international football games, just by asking questions!