Best AI tools for< Classify Data >

TextSynth is an AI tool that provides access to large language or text-to-image models through a REST API and a playground. It offers services such as text completion, question answering, classification, chat, translation, image generation, and speech-to-text transcription. The platform employs custom inference code for faster inference on standard GPUs and CPUs. Founded in 2020, TextSynth was among the first to provide access to the GPT-2 language model. While the basic service is free with rate limitations, users can opt for unlimited access by paying a small fee per request. For custom support, users can contact the platform via email.

Taylor is a deterministic AI tool that empowers Business & Engineering teams to enhance data at scale through bulk classification. It allows users to structure freeform text, enrich metadata, and customize enrichments according to specific needs. Taylor provides high impact, easy-to-use features for total control over classification and extraction models, enabling users to drive business impact from day one. With powerful integrations and simple customization options, Taylor brings powerful machine learning capabilities to users' fingertips.

AnythingLLM is an all-in-one AI application designed for everyone. It offers a comprehensive suite of tools for working with LLMs (Large Language Models), documents, and agents in a fully private manner. Users can download AnythingLLM for Desktop on Windows, MacOS, and Linux, enabling flexible one-click installation. The application supports custom model integration, including closed-source models like GPT-4 and custom fine-tuned models like Llama2. With the ability to handle various document formats beyond PDFs, AnythingLLM provides tailored solutions with locally running defaults for privacy. Additionally, users can access AnythingLLM Cloud for extended functionalities.

Imaginary Programming is an AI tool that allows frontend developers to leverage OpenAI's GPT engine to add human-like intelligence to their code effortlessly. By defining function prototypes in TypeScript, developers can access GPT's capabilities without the need for AI model training. The tool enables users to extract structured data, generate text, classify data based on intent or emotion, and parse unstructured language. Imaginary Programming is designed to help developers tackle new challenges and enhance their projects with AI intelligence.

Gamma.AI is a cloud-based data loss prevention (DLP) solution that uses artificial intelligence (AI) to protect sensitive data in SaaS applications. It provides real-time data discovery and classification, user behavior analytics, and automated remediation capabilities. Gamma.AI is designed to help organizations meet compliance requirements and protect their data from unauthorized access, theft, and loss.

Aipify is a platform that allows users to build AI-powered APIs in seconds. With Aipify, users can access the latest AI models, including GPT-4, to enhance their applications' capabilities. Aipify's APIs are easy to use and affordable, making them a great choice for businesses of all sizes.

Formula Bot Tools is a website that provides AI-powered tools for working with data and spreadsheets. The website offers a variety of generators, including an Excel formula generator, a SQL query generator, and a spreadsheet generator. It also offers a data analyzer that can help users analyze their data through a simple conversation. Additionally, the website offers AI in spreadsheets, which can help users automate boring tasks. The website is trusted by Fortune 500, government, and small and medium-sized businesses.

Takomo.ai is a no-code AI builder that allows users to connect and deploy AI models in seconds. With Takomo.ai, users can combine the best AI models in a simple visual builder to create unique AI applications. Takomo.ai offers a variety of features, including a drag-and-drop builder, pre-trained ML models, and a single API call for accessing multi-model pipelines.

FreedomGPT is a powerful AI platform that provides access to a wide range of AI models without the need for technical knowledge. With its user-friendly interface and offline capabilities, FreedomGPT empowers users to explore and utilize AI for various tasks and applications. The platform is committed to privacy and offers an open-source approach, encouraging collaboration and innovation within the AI community.

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

OpenTrain AI is a data labeling marketplace that leverages artificial intelligence to streamline the process of labeling data for machine learning models. It provides a platform where users can crowdsource data labeling tasks to a global community of annotators, ensuring high-quality labeled datasets for training AI algorithms. With advanced AI algorithms and human-in-the-loop validation, OpenTrain AI offers efficient and accurate data labeling services for various industries such as autonomous vehicles, healthcare, and natural language processing.

Cogitotech is an AI tool that specializes in data annotation and labeling expertise. The platform offers a comprehensive suite of services tailored to meet training data needs for computer vision models and AI applications. With a decade-long industry exposure, Cogitotech provides high-quality training data for industries like healthcare, financial services, security, and more. The platform helps minimize biases in AI algorithms and ensures accurate and reliable training data solutions for deploying AI in real-life systems.

Pointly is an intelligent, cloud-based B2B software solution that enables efficient automatic and advanced manual classification in 3D point clouds. It offers innovative AI techniques for fast and precise data classification and vectorization, transforming point cloud analysis into an enjoyable and efficient workflow. Pointly provides standard and custom classifiers, tools for classification and vectorization, API and on-premise classification options, collaboration features, secure cloud processing, and scalability for handling large-scale point cloud data.

OpenNN is an open-source neural networks library for machine learning that solves real-world applications in energy, marketing, health, and more. It offers sophisticated algorithms for regression, classification, forecasting, and association tasks. OpenNN provides higher capacity for managing bigger data sets and faster training compared to TensorFlow and PyTorch. It is being developed by Artelnics, a consulting company specialized in artificial intelligence and big data. Neural Designer, a software tool developed from OpenNN, helps build neural network models without programming.

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.

AnythingLLM is an all-in-one AI application designed for everyone. It offers a suite of tools for working with LLM (Large Language Models), documents, and agents in a fully private environment. Users can install AnythingLLM on their desktop for Windows, MacOS, and Linux, enabling flexible one-click installation and secure, fully private operation without internet connectivity. The application supports custom models, including enterprise models like GPT-4, custom fine-tuned models, and open-source models like Llama and Mistral. AnythingLLM allows users to work with various document formats, such as PDFs and word documents, providing tailored solutions with locally running defaults for privacy.

pgai simplifies the process of building search and Retrieval Augmented Generation (RAG) AI applications with PostgreSQL. It brings embedding and generation AI models closer to the database, allowing users to create embeddings, retrieve LLM chat completions, reason over data for classification, summarization, and data enrichment directly from within PostgreSQL in a SQL query. The tool requires an OpenAI API key and a PostgreSQL client to enable AI functionality in the database. Users can install pgai from source, run it in a pre-built Docker container, or enable it in a Timescale Cloud service. The tool provides functions to handle API keys using psql or Python, and offers various AI functionalities like tokenizing, detokenizing, embedding, chat completion, and content moderation.

Smile (Statistical Machine Intelligence and Learning Engine) is a comprehensive machine learning, NLP, linear algebra, graph, interpolation, and visualization system in Java and Scala. It covers every aspect of machine learning, including classification, regression, clustering, association rule mining, feature selection, manifold learning, multidimensional scaling, genetic algorithms, missing value imputation, efficient nearest neighbor search, etc. Smile implements major machine learning algorithms and provides interactive shells for Java, Scala, and Kotlin. It supports model serialization, data visualization using SmilePlot and declarative approach, and offers a gallery showcasing various algorithms and visualizations.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

NeMo Curator is a GPU-accelerated open-source framework designed for efficient large language model data curation. It provides scalable dataset preparation for tasks like foundation model pretraining, domain-adaptive pretraining, supervised fine-tuning, and parameter-efficient fine-tuning. The library leverages GPUs with Dask and RAPIDS to accelerate data curation, offering customizable and modular interfaces for pipeline expansion and model convergence. Key features include data download, text extraction, quality filtering, deduplication, downstream-task decontamination, distributed data classification, and PII redaction. NeMo Curator is suitable for curating high-quality datasets for large language model training.

Superagent is an open-source AI assistant framework and API that allows developers to add powerful AI assistants to their applications. These assistants use large language models (LLMs), retrieval augmented generation (RAG), and generative AI to help users with a variety of tasks, including question answering, chatbot development, content generation, data aggregation, and workflow automation. Superagent is backed by Y Combinator and is part of YC W24.

Simple Transformers is a library based on the Transformers library by HuggingFace, allowing users to quickly train and evaluate Transformer models with only 3 lines of code. It supports various tasks such as Information Retrieval, Language Models, Encoder Model Training, Sequence Classification, Token Classification, Question Answering, Language Generation, T5 Model, Seq2Seq Tasks, Multi-Modal Classification, and Conversational AI.

Lego AI Parser is an open-source application that uses OpenAI to parse visible text of HTML elements. It is built on top of FastAPI, ready to set up as a server, and make calls from any language. It supports preset parsers for Google Local Results, Amazon Listings, Etsy Listings, Wayfair Listings, BestBuy Listings, Costco Listings, Macy's Listings, and Nordstrom Listings. Users can also design custom parsers by providing prompts, examples, and details about the OpenAI model under the classifier key.

This repository is a curated list of research papers that explore the integration of Large Language Model (LLM) technology with tabular data. It aims to provide a comprehensive resource for researchers and practitioners interested in this emerging field. The repository includes papers on a wide range of topics, including table-to-text generation, table question answering, and tabular data classification. It also includes a section on related datasets and resources.

Awesome LLM Courses is a curated list of online courses focused on Large Language Models (LLMs). The repository aims to provide a comprehensive collection of free available courses covering various aspects of LLMs, including fundamentals, engineering, and applications. The courses are suitable for individuals interested in natural language processing, AI development, and machine learning. The list includes courses from reputable platforms such as Hugging Face, Udacity, DeepLearning.AI, Cohere, DataCamp, and more, offering a wide range of topics from pretraining LLMs to building AI applications with LLMs. Whether you are a beginner looking to understand the basics of LLMs or an intermediate developer interested in advanced topics like prompt engineering and generative AI, this repository has something for everyone.

sktime is a Python library for time series analysis that provides a unified interface for various time series learning tasks such as classification, regression, clustering, annotation, and forecasting. It offers time series algorithms and tools compatible with scikit-learn for building, tuning, and validating time series models. sktime aims to enhance the interoperability and usability of the time series analysis ecosystem by empowering users to apply algorithms across different tasks and providing interfaces to related libraries like scikit-learn, statsmodels, tsfresh, PyOD, and fbprophet.

ZipPy is a research repository focused on fast AI detection using compression techniques. It aims to provide a faster approximation for AI detection that is embeddable and scalable. The tool uses LZMA and zlib compression ratios to indirectly measure the perplexity of a text, allowing for the detection of low-perplexity text. By seeding a compression stream with AI-generated text and comparing the compression ratio of the seed data with the sample appended, ZipPy can identify similarities in word choice and structure to classify text as AI or human-generated.

BAML is a config file format for declaring LLM functions that you can then use in TypeScript or Python. With BAML you can Classify or Extract any structured data using Anthropic, OpenAI or local models (using Ollama) ## Resources  [Discord Community](https://discord.gg/boundaryml)  [Follow us on Twitter](https://twitter.com/boundaryml) * Discord Office Hours - Come ask us anything! We hold office hours most days (9am - 12pm PST). * Documentation - Learn BAML * Documentation - BAML Syntax Reference * Documentation - Prompt engineering tips * Boundary Studio - Observability and more #### Starter projects * BAML + NextJS 14 * BAML + FastAPI + Streaming ## Motivation Calling LLMs in your code is frustrating: * your code uses types everywhere: classes, enums, and arrays * but LLMs speak English, not types BAML makes calling LLMs easy by taking a type-first approach that lives fully in your codebase: 1. Define what your LLM output type is in a .baml file, with rich syntax to describe any field (even enum values) 2. Declare your prompt in the .baml config using those types 3. Add additional LLM config like retries or redundancy 4. Transpile the .baml files to a callable Python or TS function with a type-safe interface. (VSCode extension does this for you automatically). We were inspired by similar patterns for type safety: protobuf and OpenAPI for RPCs, Prisma and SQLAlchemy for databases. BAML guarantees type safety for LLMs and comes with tools to give you a great developer experience:  Jump to BAML code or how Flexible Parsing works without additional LLM calls. | BAML Tooling | Capabilities | | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | BAML Compiler install | Transpiles BAML code to a native Python / Typescript library (you only need it for development, never for releases) Works on Mac, Windows, Linux  | | VSCode Extension install | Syntax highlighting for BAML files Real-time prompt preview Testing UI | | Boundary Studio open (not open source) | Type-safe observability Labeling |

Bugbug is a tool developed by Mozilla that leverages machine learning techniques to assist with bug and quality management, as well as other software engineering tasks like test selection and defect prediction. It provides various classifiers to suggest assignees, detect patches likely to be backed-out, classify bugs, assign product/components, distinguish between bugs and feature requests, detect bugs needing documentation, identify invalid issues, verify bugs needing QA, detect regressions, select relevant tests, track bugs, and more. Bugbug can be trained and tested using Python scripts, and it offers the ability to run model training tasks on Taskcluster. The project structure includes modules for data mining, bug/commit feature extraction, model implementations, NLP utilities, label handling, bug history playback, and GitHub issue retrieval.

At ZenML, we believe in the importance of annotation and labeling workflows in the machine learning lifecycle. This repository showcases a curated list of open-source data annotation and labeling tools that are actively maintained and fit for purpose. The tools cover various domains such as multi-modal, text, images, audio, video, time series, and other data types. Users can contribute to the list and discover tools for tasks like named entity recognition, data annotation for machine learning, image and video annotation, text classification, sequence labeling, object detection, and more. The repository aims to help users enhance their data-centric workflows by leveraging these tools.

AITom is an open-source platform for AI-driven cellular electron cryo-tomography analysis. It is developed to process large amounts of Cryo-ET data, reconstruct, detect, classify, recover, and spatially model different cellular components using state-of-the-art machine learning approaches. The platform aims to automate cellular structure discovery and provide new insights into molecular biology and medical applications.

Marvin is a lightweight AI toolkit for building natural language interfaces that are reliable, scalable, and easy to trust. Each of Marvin's tools is simple and self-documenting, using AI to solve common but complex challenges like entity extraction, classification, and generating synthetic data. Each tool is independent and incrementally adoptable, so you can use them on their own or in combination with any other library. Marvin is also multi-modal, supporting both image and audio generation as well using images as inputs for extraction and classification. Marvin is for developers who care more about _using_ AI than _building_ AI, and we are focused on creating an exceptional developer experience. Marvin users should feel empowered to bring tightly-scoped "AI magic" into any traditional software project with just a few extra lines of code. Marvin aims to merge the best practices for building dependable, observable software with the best practices for building with generative AI into a single, easy-to-use library. It's a serious tool, but we hope you have fun with it. Marvin is open-source, free to use, and made with 💙 by the team at Prefect.

Superpipe is a lightweight framework designed for building, evaluating, and optimizing data transformation and data extraction pipelines using LLMs. It allows users to easily combine their favorite LLM libraries with Superpipe's building blocks to create pipelines tailored to their unique data and use cases. The tool facilitates rapid prototyping, evaluation, and optimization of end-to-end pipelines for tasks such as classification and evaluation of job departments based on work history. Superpipe also provides functionalities for evaluating pipeline performance, optimizing parameters for cost, accuracy, and speed, and conducting grid searches to experiment with different models and prompts.

This tool is designed to detect and classify Alzheimer's Disease using Deep Learning and Machine Learning algorithms on an early basis, which is further optimized using the Crow Search Algorithm (CSA). Alzheimer's is a fatal disease, and early detection is crucial for patients to predetermine their condition and prevent its progression. By analyzing MRI scanned images using Artificial Intelligence technology, this tool can classify patients who may or may not develop AD in the future. The CSA algorithm, combined with ML algorithms, has proven to be the most effective approach for this purpose.

Actual AI is a project designed to categorize uncategorized transactions for Actual Budget using OpenAI or OpenAI specification compatible API. It sends requests to the OpenAI API to classify transactions based on their description, amount, and notes. Transactions that cannot be classified are marked as 'not guessed' in notes. The tool allows users to sync accounts before classification and classify transactions on a cron schedule. Guessed transactions are marked in notes for easy review.

The Google Cloud Document AI Samples repository contains code samples and Community Samples demonstrating how to analyze, classify, and search documents using Google Cloud Document AI. It includes various projects showcasing different functionalities such as integrating with Google Drive, processing documents using Python, content moderation with Dialogflow CX, fraud detection, language extraction, paper summarization, tax processing pipeline, and more. The repository also provides access to test document files stored in a publicly-accessible Google Cloud Storage Bucket. Additionally, there are codelabs available for optical character recognition (OCR), form parsing, specialized processors, and managing Document AI processors. Community samples, like the PDF Annotator Sample, are also included. Contributions are welcome, and users can seek help or report issues through the repository's issues page. Please note that this repository is not an officially supported Google product and is intended for demonstrative purposes only.

Just upload a numerical dataset for classification task, will apply data analysis and machine learning steps to make a best model possible.

GPT used to classify prompts as valid inputs or injection attempts. Json output.

NACE (Nomenclature of Economic Activities) is the European statistical classification of economic activities. This is not an official product. Official information here: https://nacev2.com/en

Analyzes and categorizes perfume data from Excel, or lists. Upload a file with your perfume names or just the names of your perfumes and this GPT will help you organize the information.

Expert in LAStools with in-depth command line knowledge.

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

Analize uploaded files and assists in tasks based on their content.

Classifies articles into knowledge domains. source code: https://homun.posetmage.com/Agents/

Image & document analysis expert

Direct answers on Lie groups for the knowledgeable.

Neural Network Master V2.0

Comprehensive categorization and organization for AI Prompts

I guide on optimizing Korean sentences for embeddings.

Expert in UNSPSC Codes (United Nations Standard Products and Services Code®).

GICS is a classification standard developed by MSCI and S&P Dow Jones Indices. This GPT is not a MSCI and S&P product. Official website : https://www.msci.com/our-solutions/indexes/gics

Import Export Compliance | Tariff Classification | Shipping Queries | Logistics & Supply Chain Solutions

Expert in IATA DGR for Transportation of Dangerous Goods.

Super astronomer identifying clouds in English and Chinese, sharing facts in Chinese.

What would you say if I told you there is an app on the market that can tell you if you have a hot dog or not a hot dog.

A bilingual porcelain classification assistant.