Best AI tools for< Classify Herbs >

Trezy Classifier is a powerful API designed for transaction enrichment, categorization, and company identification. It offers global coverage, 350+ categories, VAT estimation, and more. The API goes beyond simple categorization to provide enriched data for each transaction, making it easy to relate to ledger accounts. With features like supplier intelligence, VAT estimation, and simple integration, Trezy Classifier empowers users to gain real profitability insights from their transactions.

JobtitlesAI is a machine-learning API that sorts job titles into two categories: field (sales, finance, I.T...) and position (executive, management, assistant...). It can be used in spreadsheets, Hubspot, or via API. JobtitlesAI is multilingual and GDPR compliant.

Charm is an AI-powered spreadsheet assistant that helps users clean messy data, create content, summarize feedback, classify sales leads, and generate dummy data. It is a Google Sheets add-on that automates tasks that are impossible to do with traditional formulas. Charm is used by hundreds of analysts, marketers, product managers, and more.

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.

Taylor is a deterministic AI tool that empowers Business & Engineering teams to enrich and automate text data at scale. It allows users to structure freeform text, customize enrichments, and build classification models for real-time data pipelines. With easy customization and integration capabilities, Taylor brings powerful machine learning to streamline business operations and product features.

FranzAI LLM Playground is an AI-powered tool that helps you extract, classify, and analyze unstructured text data. It leverages transformer models to provide accurate and meaningful results, enabling you to build data applications faster and more efficiently. With FranzAI, you can accelerate product and content classification, enhance data interpretation, and advance data extraction processes, unlocking key insights from your textual data.

Eigen Technologies is an AI-powered data extraction platform designed for business users to automate the extraction of data from various documents. The platform offers solutions for intelligent document processing and automation, enabling users to streamline business processes, make informed decisions, and achieve significant efficiency gains. Eigen's platform is purpose-built to deliver real ROI by reducing manual processes, improving data accuracy, and accelerating decision-making across industries such as corporates, banks, financial services, insurance, law, and manufacturing. With features like generative insights, table extraction, pre-processing hub, and model governance, Eigen empowers users to automate data extraction workflows efficiently. The platform is known for its unmatched accuracy, speed, and capability, providing customers with a flexible and scalable solution that integrates seamlessly with existing systems.

Nightfall AI is an all-in-one data loss prevention platform that leverages AI technology to prevent data leaks and insider risks. The platform offers features such as human firewall, AI-native detection, extensible workflows, data encryption, data discovery & classification, and firewall for AI. Nightfall AI helps organizations safeguard sensitive data, prevent data exfiltration, and secure personal information across various industries and compliance standards. With a focus on modern data security challenges, Nightfall AI provides automated data protection solutions that are easy, fast, and effective.

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.

Roboflow is a platform that provides tools for building and deploying computer vision models. It offers a range of features, including data annotation, model training, and deployment. Roboflow is used by over 250,000 engineers to create datasets, train models, and deploy to production.

Cohere is a leading provider of artificial intelligence (AI) tools and services. Our mission is to make AI accessible and useful to everyone, from individual developers to large enterprises. We offer a range of AI tools and services, including natural language processing, computer vision, and machine learning. Our tools are used by businesses of all sizes to improve customer service, automate tasks, and gain insights from data.

Hive AI provides a suite of AI models and solutions for understanding, searching, and generating content. Their AI models can be integrated into applications via APIs, enabling developers to add advanced content understanding capabilities to their products. Hive AI's solutions are used by businesses in various industries, including digital platforms, sports, media, and marketing, to streamline content moderation, automate image search and authentication, measure sponsorships, and monetize ad inventory.

Predibase is a platform for fine-tuning and serving Large Language Models (LLMs). It provides a cost-effective and efficient way to train and deploy LLMs for a variety of tasks, including classification, information extraction, customer sentiment analysis, customer support, code generation, and named entity recognition. Predibase is built on proven open-source technology, including LoRAX, Ludwig, and Horovod.

Levity is an AI-powered email automation tool designed specifically for the freight industry. It connects to your inbox, categorizes incoming emails, extracts critical information, and pushes it to your TMS, allowing you to focus on building customer relationships instead of manual data entry and repetitive tasks.

Liner is a free and easy-to-use tool that allows users to train machine learning models without writing any code. It provides a user-friendly interface that guides users through the process of importing data, selecting a model, and training the model. Liner also offers a variety of pre-trained models that can be used for common tasks such as image classification, text classification, and object detection. With Liner, users can quickly and easily create and deploy machine learning applications without the need for specialized knowledge or expertise.

Cogniflow is a no-code AI platform that allows users to build and deploy custom AI models without any coding experience. The platform provides a variety of pre-built AI models that can be used for a variety of tasks, including customer service, HR, operations, and more. Cogniflow also offers a variety of integrations with other applications, making it easy to connect your AI models to your existing workflow.

Landing AI is a computer vision platform and AI software company that provides a cloud-based platform for building and deploying computer vision applications. The platform includes a library of pre-trained models, a set of tools for data labeling and model training, and a deployment service that allows users to deploy their models to the cloud or edge devices. Landing AI's platform is used by a variety of industries, including automotive, electronics, food and beverage, medical devices, life sciences, agriculture, manufacturing, infrastructure, and pharma.

This website provides a platform for users to apply artificial intelligence (AI) to their work. Users can access a variety of AI tools and resources, including pre-trained models, datasets, and tutorials. The website also provides a community forum where users can connect with other AI enthusiasts and experts.

Custom Vision is a cognitive service provided by Microsoft that offers a user-friendly platform for creating custom computer vision models. Users can easily train the models by providing labeled images, allowing them to tailor the models to their specific needs. The service simplifies the process of implementing visual intelligence into applications, making it accessible even to those without extensive machine learning expertise.

Nesa is a global blockchain network that brings AI on-chain, allowing applications and protocols to seamlessly integrate with AI. It offers secure execution for critical inference, a private AI network, and a global AI model repository. Nesa supports various AI models for tasks like text classification, content summarization, image generation, language translation, and more. The platform is backed by a team with extensive experience in AI and deep learning, with numerous awards and recognitions in the field.

HuaTuoAI is an artificial intelligence image classification system specifically designed for traditional Chinese medicine. It utilizes deep learning techniques, such as Convolutional Neural Networks (CNN), to accurately classify Chinese herbs and ingredients based on input images. The project aims to unlock the secrets of plants, depict the unknown realm of Chinese medicine using technology and intelligence, and perpetuate ancient cultural heritage.

The Open MatSci ML Toolkit is a flexible framework for machine learning in materials science. It provides a unified interface to a variety of materials science datasets, as well as a set of tools for data preprocessing, model training, and evaluation. The toolkit is designed to be easy to use for both beginners and experienced researchers, and it can be used to train models for a wide range of tasks, including property prediction, materials discovery, and materials design.

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.

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.

This repository contains code for the AI challenger competition on plant disease detection. The goal is to classify nearly 50,000 plant leaf photos into 61 categories based on 'species-disease-severity'. The framework used is Keras with TensorFlow backend, implementing DenseNet for image classification. Data is uploaded to a private dataset on Kaggle for model training. The code includes data preparation, model training, and prediction steps.

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.

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.

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.

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.

The Aleph Alpha Intelligence Layer️ offers a comprehensive suite of development tools for crafting solutions that harness the capabilities of large language models (LLMs). With a unified framework for LLM-based workflows, it facilitates seamless AI product development, from prototyping and prompt experimentation to result evaluation and deployment. The Intelligence Layer SDK provides features such as Composability, Evaluability, and Traceability, along with examples to get started. It supports local installation using poetry, integration with Docker, and access to LLM endpoints for tutorials and tasks like Summarization, Question Answering, Classification, Evaluation, and Parameter Optimization. The tool also offers pre-configured tasks for tasks like Classify, QA, Search, and Summarize, serving as a foundation for custom development.

CAPPr is a tool for text classification that does not require training or post-processing. It allows users to have their language models pick from a list of choices or compute the probability of a completion given a prompt. The tool aims to help users get more out of open source language models by simplifying the text classification process. CAPPr can be used with GGUF models, Hugging Face models, models from the OpenAI API, and for tasks like caching instructions, extracting final answers from step-by-step completions, and running predictions in batches with different sets of completions.

Instructor is a tool designed to structure outputs from OpenAI and other OSS LLMs by coaxing them to return JSON that maps to a provided Ecto schema. It allows for defining validation logic to guide LLMs in making corrections, and supports automatic retries. Instructor is primarily used with the OpenAI API but can be extended to work with other platforms. The tool simplifies usage by creating an ecto schema, defining a validation function, and making calls to chat_completion with instructions for the LLM. It also offers features like max_retries to fix validation errors iteratively.

MediaPipe-rs is a Rust library designed for MediaPipe tasks on WasmEdge WASI-NN. It offers easy-to-use low-code APIs similar to mediapipe-python, with low overhead and flexibility for custom media input. The library supports various tasks like object detection, image classification, gesture recognition, and more, including TfLite models, TF Hub models, and custom models. Users can create task instances, run sessions for pre-processing, inference, and post-processing, and speed up processing by reusing sessions. The library also provides support for audio tasks using audio data from symphonia, ffmpeg, or raw audio. Users can choose between CPU, GPU, or TPU devices for processing.

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.

Semantic Cache is a tool for caching natural text based on semantic similarity. It allows for classifying text into categories, caching AI responses, and reducing API latency by responding to similar queries with cached values. The tool stores cache entries by meaning, handles synonyms, supports multiple languages, understands complex queries, and offers easy integration with Node.js applications. Users can set a custom proximity threshold for filtering results. The tool is ideal for tasks involving querying or retrieving information based on meaning, such as natural language classification or caching AI responses.

FlashLearn is a tool that provides a simple interface and orchestration for incorporating Agent LLMs into workflows and ETL pipelines. It allows data transformations, classifications, summarizations, rewriting, and custom multi-step tasks using LLMs. Each step and task has a compact JSON definition, making pipelines easy to understand and maintain. FlashLearn supports LiteLLM, Ollama, OpenAI, DeepSeek, and other OpenAI-compatible clients.

Ultralytics YOLO for Flutter is a Flutter plugin that allows you to integrate Ultralytics YOLO computer vision models into your mobile apps. It supports both Android and iOS platforms, providing APIs for object detection and image classification. The plugin leverages Flutter Platform Channels for seamless communication between the client and host, handling all processing natively. Before using the plugin, you need to export the required models in `.tflite` and `.mlmodel` formats. The plugin provides support for tasks like detection and classification, with specific instructions for Android and iOS platforms. It also includes features like camera preview and methods for object detection and image classification on images. Ultralytics YOLO thrives on community collaboration and offers different licensing paths for open-source and commercial use cases.

This repository contains a collection of code samples that demonstrate how to use various Azure AI capabilities to process documents. The samples help engineering teams establish techniques with Azure AI Foundry, Azure OpenAI, Azure AI Document Intelligence, and Azure AI Language services to build solutions for extracting structured data, classifying, and analyzing documents. The techniques simplify custom model training, improve reliability in document processing, and simplify document processing workflows by providing reusable code and patterns that can be easily modified and evaluated for most use cases.

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

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

Expert in LAStools with in-depth command line knowledge.

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

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

Expert in IATA DGR for Transportation of Dangerous Goods.

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

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

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.

Direct answers on Lie groups for the knowledgeable.

A bilingual porcelain classification assistant.

Medical Device Expert on MDR 2017/745, IVDR 2017/746 and related MDCG guidance

Assists in identifying wildlife.

I guide on optimizing Korean sentences for embeddings.

guess the era of the image!

I identify various rocks from images and advise consulting a geologist for certainty.

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