Best AI tools for< Feature Extraction >

Janus Pro AI is an advanced unified multimodal AI model that combines image understanding and generation capabilities. It incorporates optimized training strategies, expanded training data, and larger model scaling to achieve significant advancements in both multimodal understanding and text-to-image generation tasks. Janus Pro features a decoupled visual encoding system, outperforming leading models like DALL-E 3 and Stable Diffusion in benchmark tests. It offers open-source compatibility, vision processing specifications, cost-effective scalability, and an optimized training framework.

X Detector is a free AI content detector and checker that accurately identifies whether a text is AI-generated or human-written. It leverages advanced detection strategies, including corpus-based comparison, language model analysis, feature extraction, and plagiarism detection, to achieve over 99% accuracy. The tool supports multiple languages, ensures data security with Web3 encryption, and has been widely acclaimed for its reliability and efficiency. X Detector is ideal for students, teachers, writers, and institutions to maintain academic integrity, prevent plagiarism, and verify the authenticity of written content.

Walle is an all-in-one AI assistant and browser extension that provides a range of features to enhance your digital experience. It includes a chatbot for instant problem-solving, an AI reader for summarizing and understanding text, an AI writer for generating human-like content, a chat PDF feature for summarizing and translating PDF documents, and image creation and reading capabilities. Walle is seamlessly integrated into Chrome, Safari, and Edge browsers, making it your indispensable companion for navigating the digital world.

Lexalytics is a leading provider of text analytics and natural language processing (NLP) solutions. Our platform and services help businesses transform complex text data into valuable insights and actionable intelligence. With Lexalytics, you can: * **Analyze customer feedback** to understand what your customers are saying about your products, services, and brand. * **Identify trends and patterns** in text data to make better decisions about your business. * **Automate tasks** such as document classification, entity extraction, and sentiment analysis. * **Develop custom NLP applications** to meet your specific needs.

CustomerIQ is an AI platform that automatically discovers and quantifies themes across customer feedback channels like calls, surveys, tickets, and transcripts. It aggregates customer feedback, extracts and categorizes feature requests, pain points, preferences, and highlights related to customers. The platform helps align teams, prioritize work, and build a customer-obsessed culture. CustomerIQ accelerates development by scoping project requirements faster and providing actionable insights backed with context.

Inkwise is an AI-powered platform that helps users craft expert documents by extracting and integrating key information seamlessly from uploaded files. The platform offers features such as smart content extraction, predictive writing, document templates, and AI chat with files. Inkwise automates the document creation process by analyzing uploaded documents, extracting relevant data, and integrating it into customizable templates. It caters to various professions including academics, accounting, finance, corporate treasury, corporate tax, product management, procurement, legal, and marketing.

Airparser is an AI-powered email and document parser tool that revolutionizes data extraction by utilizing the GPT parser engine. It allows users to automate the extraction of structured data from various sources such as emails, PDFs, documents, and handwritten texts. With features like automatic extraction, export to multiple platforms, and support for multiple languages, Airparser simplifies data extraction processes for individuals and businesses. The tool ensures data security and offers seamless integration with other applications through APIs and webhooks.

Improvado is an AI-powered marketing analytics and intelligence platform that empowers enterprises and agencies to automate complex campaign reporting, make data-driven decisions, and leverage AI to optimize performance and drive ROI. It offers a range of features including data extraction, data ownership, data transformation, business data QA, instant intelligence, data sources, data warehouses, reporting tools, AI Agent, and more. Improvado's advantages include automating complex campaign reporting, enabling data-driven decision-making, leveraging AI for optimization, providing in-depth insights, offering advanced attribution, budget pacing, and ensuring security and compliance.

LM-Kit.NET is a comprehensive AI toolkit for .NET developers, offering a wide range of features such as AI agent integration, data processing, text analysis, translation, text generation, and model optimization. The toolkit enables developers to create intelligent and adaptable AI applications by providing tools for language models, sentiment analysis, emotion detection, and more. With a focus on performance optimization and security, LM-Kit.NET empowers developers to build cutting-edge AI solutions seamlessly into their C# and VB.NET applications.

Kudra is an AI-powered data extraction tool that offers dedicated solutions for finance, human resources, logistics, legal, and more. It effortlessly extracts critical data fields, tables, relationships, and summaries from various documents, transforming unstructured data into actionable insights. Kudra provides customizable AI models, seamless integrations, and secure document processing while supporting over 20 languages. With features like custom workflows, model training, API integration, and workflow builder, Kudra aims to streamline document processing for businesses of all sizes.

AgentQL is an AI-powered tool for painless data extraction and web automation. It eliminates the need for fragile XPath or DOM selectors by using semantic selectors and natural language descriptions to find web elements reliably. With controlled output and deterministic behavior, AgentQL allows users to shape data exactly as needed. The tool offers features such as extracting data, filling forms automatically, and streamlining testing processes. It is designed to be user-friendly and efficient for developers and data engineers.

Dataku.ai is an advanced data extraction and analysis tool powered by AI technology. It offers seamless extraction of valuable insights from documents and texts, transforming unstructured data into structured, actionable information. The tool provides tailored data extraction solutions for various needs, such as resume extraction for streamlined recruitment processes, review insights for decoding customer sentiments, and leveraging customer data to personalize experiences. With features like market trend analysis and financial document analysis, Dataku.ai empowers users to make strategic decisions based on accurate data. The tool ensures precision, efficiency, and scalability in data processing, offering different pricing plans to cater to different user needs.

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.

Receipt OCR API by ReceiptUp is an advanced tool that leverages OCR and AI technology to extract structured data from receipt and invoice images. The API offers high accuracy and multilingual support, making it ideal for businesses worldwide to streamline financial operations. With features like multilingual support, high accuracy, support for multiple formats, accounting downloads, and affordability, Receipt OCR API is a powerful tool for efficient receipt management and data extraction.

Speck is a web automation tool that simplifies web data extraction using AI technology. It allows users to record their workflows and then automate the process with the help of an AI copilot. Speck learns from user interactions, ensuring efficient data extraction without the need for constant manual adjustments. The tool offers features such as custom workflow automation, web data supercharger, smart browser navigation, intelligent form filler, and interactive web tutorials. Speck is designed to streamline web tasks and enhance productivity by automating repetitive processes.

MapsScraperAI is an AI-powered tool designed to extract leads and data from Maps. It offers businesses the ability to generate local B2B leads, conduct research, monitor competition, and obtain business contact details. With features like batch lookup, lightning-fast results, and the unique ability to extract email addresses, MapsScraperAI streamlines the process of data extraction without the need for coding. The tool mimics real user behavior to reduce the risk of being blocked by Maps and ensures timely updates to accommodate any changes on the Maps website.

Apify is a full-stack web scraping and data extraction platform that provides developers with tools to build, deploy, and publish web scrapers, AI agents, and automation tools. The platform offers pre-built web scraping tools, serverless program execution, integrations with various apps and services, storage for scraper results, anti-blocking features, and open-source web scraping and crawling libraries.

Octoparse is an AI web scraping tool that offers a no-coding solution for turning web pages into structured data with just a few clicks. It provides users with the ability to build reliable web scrapers without any coding knowledge, thanks to its intuitive workflow designer. With features like AI assistance, automation, and template libraries, Octoparse is a powerful tool for data extraction and analysis across various industries.

Floom.ai is an AI Marketplace for apps that allows users to easily add AI functions to their applications in just 5 minutes, without requiring any prior AI knowledge. The platform offers a variety of AI functions developed by the community, such as text translation, classification, summarization, keyword extraction, social media post generation, code explanation, code conversion, code improvement, physical address extraction, and SQL query generation. Floom.ai aims to empower developers and businesses to enhance their applications with AI capabilities through a user-friendly and efficient marketplace.

Doclingo is an AI-powered document translation tool that supports translating documents in various formats such as PDF, Word, Excel, PowerPoint, SRT subtitles, ePub ebooks, AR&ZIP packages, and more. It utilizes large language models to provide accurate and professional translations, preserving the original layout of the documents. Users can enjoy a limited-time free trial upon registration, with the option to subscribe for more features. Doclingo aims to offer high-quality translation services through continuous algorithm improvements.

Plug-play-modules is a comprehensive collection of plug-and-play modules for AI, deep learning, and computer vision applications. It includes various convolution variants, latest attention mechanisms, feature fusion modules, up-sampling/down-sampling modules, suitable for tasks like image classification, object detection, instance segmentation, semantic segmentation, single object tracking (SOT), multi-object tracking (MOT), infrared object tracking (RGBT), image de-raining, de-fogging, de-blurring, super-resolution, and more. The modules are designed to enhance model performance and feature extraction capabilities across various tasks.

Indexify is an open-source engine for building fast data pipelines for unstructured data (video, audio, images, and documents) using reusable extractors for embedding, transformation, and feature extraction. LLM Applications can query transformed content friendly to LLMs by semantic search and SQL queries. Indexify keeps vector databases and structured databases (PostgreSQL) updated by automatically invoking the pipelines as new data is ingested into the system from external data sources. **Why use Indexify** * Makes Unstructured Data **Queryable** with **SQL** and **Semantic Search** * **Real-Time** Extraction Engine to keep indexes **automatically** updated as new data is ingested. * Create **Extraction Graph** to describe **data transformation** and extraction of **embedding** and **structured extraction**. * **Incremental Extraction** and **Selective Deletion** when content is deleted or updated. * **Extractor SDK** allows adding new extraction capabilities, and many readily available extractors for **PDF**, **Image**, and **Video** indexing and extraction. * Works with **any LLM Framework** including **Langchain**, **DSPy**, etc. * Runs on your laptop during **prototyping** and also scales to **1000s of machines** on the cloud. * Works with many **Blob Stores**, **Vector Stores**, and **Structured Databases** * We have even **Open Sourced Automation** to deploy to Kubernetes in production.

This repository provides code for extracting image and text features using OpenAI CLIP models, supporting both global and local grid visual features. It aims to facilitate multi visual-and-language downstream tasks by allowing users to customize input and output grid resolution easily. The extracted features have shown comparable or superior results in image captioning tasks without hyperparameter tuning. The repo supports various CLIP models and provides detailed information on supported settings and results on MSCOCO image captioning. Users can get started by setting up experiments with the extracted features using X-modaler.

The `sec-parser` project simplifies extracting meaningful information from SEC EDGAR HTML documents by organizing them into semantic elements and a tree structure. It helps in parsing SEC filings for financial and regulatory analysis, analytics and data science, AI and machine learning, causal AI, and large language models. The tool is especially beneficial for AI, ML, and LLM applications by streamlining data pre-processing and feature extraction.

Lhotse is a Python library designed to make speech and audio data preparation flexible and accessible. It aims to attract a wider community to speech processing tasks by providing a Python-centric design and an expressive command-line interface. Lhotse offers standard data preparation recipes, PyTorch Dataset classes for speech tasks, and efficient data preparation for model training with audio cuts. It supports data augmentation, feature extraction, and feature-space cut mixing. The tool extends Kaldi's data preparation recipes with seamless PyTorch integration, human-readable text manifests, and convenient Python classes.

VideoTree is an official implementation for a query-adaptive and hierarchical framework for understanding long videos with LLMs. It dynamically extracts query-related information from input videos and builds a tree-based video representation for LLM reasoning. The tool requires Python 3.8 or above and leverages models like LaViLa and EVA-CLIP-8B for feature extraction. It also provides scripts for tasks like Adaptive Breath Expansion, Relevance-based Depth Expansion, and LLM Reasoning. The codebase is being updated to incorporate scripts/captions for NeXT-QA and IntentQA in the future.

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.

MLP Mixer - Pytorch is an all-MLP solution for vision tasks, developed by Google AI, implemented in Pytorch. It provides an architecture that does not require convolutions or attention mechanisms, offering an alternative approach for image and video processing. The tool is designed to handle tasks related to image classification and video recognition, utilizing multi-layer perceptrons (MLPs) for feature extraction and classification. Users can easily install the tool using pip and integrate it into their Pytorch projects to experiment with MLP-based vision models.

This repository is a collection of papers on leveraging Large Language Models (LLMs) in Graph Tasks. It provides a comprehensive overview of how LLMs can enhance graph-related tasks by combining them with traditional Graph Neural Networks (GNNs). The integration of LLMs with GNNs allows for capturing both structural and contextual aspects of nodes in graph data, leading to more powerful graph learning. The repository includes summaries of various models that leverage LLMs to assist in graph-related tasks, along with links to papers and code repositories for further exploration.

This project focuses on implementing Sparse Autoencoders (SAEs) for mechanistic interpretability in Large Language Models (LLMs) like Llama 3.2-3B. The SAEs aim to untangle superimposed representations in LLMs into separate, interpretable features for each neuron activation. The project provides an end-to-end pipeline for capturing training data, training the SAEs, analyzing learned features, and verifying results experimentally. It includes comprehensive logging, visualization, and checkpointing of SAE training, interpretability analysis tools, and a pure PyTorch implementation of Llama 3.1/3.2 chat and text completion. The project is designed for scalability, efficiency, and maintainability.

SemanticFinder is a frontend-only live semantic search tool that calculates embeddings and cosine similarity client-side using transformers.js and SOTA embedding models from Huggingface. It allows users to search through large texts like books with pre-indexed examples, customize search parameters, and offers data privacy by keeping input text in the browser. The tool can be used for basic search tasks, analyzing texts for recurring themes, and has potential integrations with various applications like wikis, chat apps, and personal history search. It also provides options for building browser extensions and future ideas for further enhancements and integrations.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

Vearch is a cloud-native distributed vector database designed for efficient similarity search of embedding vectors in AI applications. It supports hybrid search with vector search and scalar filtering, offers fast vector retrieval from millions of objects in milliseconds, and ensures scalability and reliability through replication and elastic scaling out. Users can deploy Vearch cluster on Kubernetes, add charts from the repository or locally, start with Docker-compose, or compile from source code. The tool includes components like Master for schema management, Router for RESTful API, and PartitionServer for hosting document partitions with raft-based replication. Vearch can be used for building visual search systems for indexing images and offers a Python SDK for easy installation and usage. The tool is suitable for AI developers and researchers looking for efficient vector search capabilities in their applications.

LLMs4TS is a repository focused on the application of cutting-edge AI technologies for time-series analysis. It covers advanced topics such as self-supervised learning, Graph Neural Networks for Time Series, Large Language Models for Time Series, Diffusion models, Mixture-of-Experts architectures, and Mamba models. The resources in this repository span various domains like healthcare, finance, and traffic, offering tutorials, courses, and workshops from prestigious conferences. Whether you're a professional, data scientist, or researcher, the tools and techniques in this repository can enhance your time-series data analysis capabilities.

Nmed2024 is a GitHub repository that contains code for a neural network model designed for medical image analysis. The repository includes scripts for training the model, as well as pre-trained weights for quick deployment. The model is specifically tailored for detecting abnormalities in medical images, such as tumors or fractures. It utilizes deep learning techniques to achieve high accuracy and can be easily integrated into existing medical imaging systems. Researchers and developers in the healthcare industry can leverage this tool to enhance the efficiency and accuracy of medical image analysis tasks.

geoai is a Python package designed for utilizing Artificial Intelligence (AI) in the context of geospatial data. It allows users to visualize various types of geospatial data such as vector, raster, and LiDAR data. Additionally, the package offers functionalities for segmenting remote sensing imagery using the Segment Anything Model and classifying remote sensing imagery with deep learning models. With a focus on geospatial AI applications, geoai provides a versatile tool for processing and analyzing spatial data with the power of AI.

Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

This GPT writes tickets for software features. It uses Gherkin to specify scenarios. @cxmacedo

Upload your dataset, and I'll assist with feature engineering.

SEO Expert in Product Feature Optimization. Specializes in crafting detailed, SEO-enhanced lists that highlight unique selling points for optimal search visibility. Balances technical SEO with user engagement, providing clear, accurate, relevant lists for immediate use.

Creates Reforge framework feature maps in tabular format.

Guides on GPT Builder's Action feature and API usage

Create professional grade feature stories with user inputs

Helps you create feature stories for your products.

Guides through product feature development and spec writing

All things money. Feature in testing: Reports with memory system. ZERO SHOT REPORTS V0.3 (BETA)

Your article formatting expert with Word download link feature.

A guide for creating GPT apps with a new monetization feature.

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Live translation between two users speaking different languages - This GPT is designed for the voice feature in the OpenAI App

Adds Hogwarts magic to photos, with interactive Sorting Hat feature.

This GPT can generate code for you. For now it creates full-stack apps using Typescript. Just describe the feature you want and you will get a link to the Github code pull request and the live app deployed.

Bible Software Tool Hebrew Greek Aramaic - Delving deep into Bible languages and meanings. Languages including Hebrew, Greek and Aramaic. Send feature requests or feedback via ChatGPT or email [email protected] for chance to win draws)

I'm a ransomware negotiation simulation and analysis bot trained with over 131 real-life negotiations. Type "start negotiation" to begin! New feature: Type "threat actor personality test"

Friendly, professional assistant for laptop or PC issues, with image analysis feature.

Senior TypeScript Programmer with expertise in Node.js, React, and Redux.

Garden design, upload photos to communicate the design of your garden