Best AI tools for< Implement Nlp Features >

Kavita Ganesan's website offers a range of resources and services related to AI, including AI strategy books, tips for AI success, data science and NLP tutorials, speaking engagements, workshops, AI consulting, and more. The site aims to help businesses leverage AI to gain a competitive advantage and maximize success through proven strategies and frameworks.

LlamaIndex is a framework for building context-augmented Large Language Model (LLM) applications. It provides tools to ingest and process data, implement complex query workflows, and build applications like question-answering chatbots, document understanding systems, and autonomous agents. LlamaIndex enables context augmentation by combining LLMs with private or domain-specific data, offering tools for data connectors, data indexes, engines for natural language access, chat engines, agents, and observability/evaluation integrations. It caters to users of all levels, from beginners to advanced developers, and is available in Python and Typescript.

Inspect is an open-source framework for large language model evaluations created by the UK AI Safety Institute. It provides built-in components for prompt engineering, tool usage, multi-turn dialog, and model graded evaluations. Users can explore various solvers, tools, scorers, datasets, and models to create advanced evaluations. Inspect supports extensions for new elicitation and scoring techniques through Python packages.

Digital Sense is an AI tool that offers a wide range of AI, Machine Learning, and Computer Vision services. The company specializes in custom AI development, AI consulting services, biometrics solutions, NLP & LLMs development services, data science consulting services, remote sensing services, machine learning development services, generative AI development services, and computer vision development services. With over a decade of experience, Digital Sense helps businesses leverage cutting-edge AI technologies to solve complex technological challenges.

Beebzi.AI is an all-in-one AI content creation platform that offers a wide array of tools for generating various types of content such as articles, blogs, emails, images, voiceovers, and more. The platform utilizes advanced AI technology and behavioral science to empower businesses and individuals in their marketing and sales endeavors. With features like AI Article Wizard, AI Room Designer, AI Landing Page Generator, and AI Code Generation, Beebzi.AI revolutionizes content creation by providing customizable templates, multiple language support, and real-time data insights. The platform also offers various subscription plans tailored for individual entrepreneurs, teams, and businesses, with flexible pricing models based on word count allocations. Beebzi.AI aims to streamline content creation processes, enhance productivity, and drive organic traffic through SEO-optimized content.

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.

Palo Alto Networks is a cybersecurity company offering advanced security solutions powered by Precision AI to protect modern enterprises from cyber threats. The company provides network security, cloud security, and AI-driven security operations to defend against AI-generated threats in real time. Palo Alto Networks aims to simplify security and achieve better security outcomes through platformization, intelligence-driven expertise, and proactive monitoring of sophisticated threats.

Ringover is an AI-driven conversation platform designed for staffing and sales teams. It offers features such as transcription and call summaries, mood analysis, cloud telephony, multichannel communications, sales prospecting automations, app marketplace integration, and more. The platform aims to centralize all communication channels within a simple interface, empowering users to enhance productivity and streamline conversations with clients and prospects. Ringover also provides advanced analytics, automation, and coaching to boost the productivity of recruiting and sales teams. With seamless integration with various business tools, Ringover offers a comprehensive solution for businesses looking to optimize their communication strategies.

RankSense is an AI-powered SEO tool designed to help users optimize their website's search engine performance efficiently. Created by Hamlet Batista, RankSense enables users to implement immediate changes to SEO meta tags, structured data, and redirects at scale. By leveraging Cloudflare and Google Sheets, users can make SEO changes on thousands of pages with just a few clicks, without the need for developers. The tool also offers features such as monitoring SEO changes, discovering pages that need optimization, and automatically improving search snippets using artificial intelligence.

RIOS is an AI-powered automation tool that revolutionizes American manufacturing by leveraging robotics and AI technology. It offers flexible, reliable, and efficient robotic automation solutions that integrate seamlessly into existing production lines, helping businesses improve productivity, reduce operating expenses, and minimize risks. RIOS provides intelligent agents, machine tending, food handling, and end-of-line packout services, powered by AI and robotics. The tool aims to simplify complex manual processes, ensure total control of operations, and cut costs for businesses facing production inefficiencies and challenges in labor productivity.

Cue AI is an AI research lab dedicated to enhancing the capabilities of cutting-edge models. The lab is committed to pushing the boundaries of AI technology and innovation. While the website currently has limited information, it serves as a platform for sharing updates and developments in the field of artificial intelligence. For inquiries or collaborations, users can reach out via email at [email protected].

Faculty AI is a leading applied AI consultancy and technology provider, specializing in helping customers transform their businesses through bespoke AI consultancy and Frontier, the world's first AI operating system. They offer services such as AI consultancy, generative AI solutions, and AI services tailored to various industries. Faculty AI is known for its expertise in AI governance and safety, as well as its partnerships with top AI platforms like OpenAI, AWS, and Microsoft.

Modulos is a Responsible AI Platform that integrates risk management, data science, legal compliance, and governance principles to ensure responsible innovation and adherence to industry standards. It offers a comprehensive solution for organizations to effectively manage AI risks and regulations, streamline AI governance, and achieve relevant certifications faster. With a focus on compliance by design, Modulos helps organizations implement robust AI governance frameworks, execute real use cases, and integrate essential governance and compliance checks throughout the AI life cycle.

Papers With Code is an AI tool that provides access to the latest research papers in the field of Machine Learning, along with corresponding code implementations. It offers a platform for researchers and enthusiasts to stay updated on state-of-the-art datasets, methods, and trends in the ML domain. Users can explore a wide range of topics such as language modeling, image generation, virtual try-on, and more through the collection of papers and code available on the website.

Lifestyle Medicine WORKS™ PRO AI is a comprehensive AI-powered platform designed for physicians, healthcare providers, and clinics worldwide. It offers tools and courses to master evidence-based Lifestyle Medicine, reduce team burnout, save time, create new revenue opportunities, and improve chronic diseases patient health outcomes. The platform includes 6 AI Assistants, a 101 Course, business strategies, certification, and more. Lifestyle Medicine WORKS™ PRO AI aims to empower healthcare professionals to seamlessly integrate evidence-based Lifestyle Medicine into their practice and help patients prevent, reduce, and even reverse chronic symptoms.

SentiSight.ai is a machine learning platform for image recognition solutions, offering services such as object detection, image segmentation, image classification, image similarity search, image annotation, computer vision consulting, and intelligent automation consulting. Users can access pre-trained models, background removal, NSFW detection, text recognition, and image recognition API. The platform provides tools for image labeling, project management, and training tutorials for various image recognition models. SentiSight.ai aims to streamline the image annotation process, empower users to build and train their own models, and deploy them for online or offline use.

Demand Spring is a strategic AI implementation platform for B2B marketing leaders. They offer services such as AI advisory for revenue acceleration, AI activation & growth services, training & enablement for AI-first mindset teams, and marketing automation & AI workflow agents. The platform helps B2B marketing leaders leverage AI and marketing automation platforms to transform operations, increase productivity, and create personalized customer engagement. Demand Spring aims to make AI and automation accessible, actionable, and impactful for their clients.

Notice is an AI-powered platform that allows users to create blogs, documents, portfolios, and more with ease. It offers collaborative editing, auto-translation in over 100 languages, and an AI writing assistant. Users can embed their content anywhere on the web using ready-to-use templates that are SEO-friendly. Notice simplifies content creation and publishing, making it accessible to users of all skill levels.

The Transparency Coalition is a platform dedicated to advocating for legislation and transparency in the field of artificial intelligence. It aims to create AI safeguards for the greater good by focusing on training data, accountability, and ethical practices in AI development and deployment. The platform emphasizes the importance of regulating training data to prevent misuse and harm caused by AI systems. Through advocacy and education, the Transparency Coalition seeks to promote responsible AI innovation and protect personal privacy.

Rebecca Bultsma is a trusted and experienced AI educator who aims to make AI simple and ethical for everyday use. She provides resources, speaking engagements, and consulting services to help individuals and organizations understand and integrate AI into their workflows. Rebecca empowers people to work in harmony with AI, leveraging its capabilities to tackle challenges, spark creative ideas, and make a lasting impact. She focuses on making AI easy to understand and promoting ethical adoption strategies.

chatgpt.js-chrome-starter is a starting point for developing Chrome extensions using chatgpt.js. It provides a template with installation instructions and tips for creating extensions that leverage the ChatGPT technology. The repository includes sample screenshots and references to advanced Chrome API methods for developers to explore.

LightRAG is a repository hosting the code for LightRAG, a system that supports seamless integration of custom knowledge graphs, Oracle Database 23ai, Neo4J for storage, and multiple file types. It includes features like entity deletion, batch insert, incremental insert, and graph visualization. LightRAG provides an API server implementation for RESTful API access to RAG operations, allowing users to interact with it through HTTP requests. The repository also includes evaluation scripts, code for reproducing results, and a comprehensive code structure.

LLMeBench is a flexible framework designed for accelerating benchmarking of Large Language Models (LLMs) in the field of Natural Language Processing (NLP). It supports evaluation of various NLP tasks using model providers like OpenAI, HuggingFace Inference API, and Petals. The framework is customizable for different NLP tasks, LLM models, and datasets across multiple languages. It features extensive caching capabilities, supports zero- and few-shot learning paradigms, and allows on-the-fly dataset download and caching. LLMeBench is open-source and continuously expanding to support new models accessible through APIs.

MindNLP is an open-source NLP library based on MindSpore. It provides a platform for solving natural language processing tasks, containing many common approaches in NLP. It can help researchers and developers to construct and train models more conveniently and rapidly. Key features of MindNLP include: * Comprehensive data processing: Several classical NLP datasets are packaged into a friendly module for easy use, such as Multi30k, SQuAD, CoNLL, etc. * Friendly NLP model toolset: MindNLP provides various configurable components. It is friendly to customize models using MindNLP. * Easy-to-use engine: MindNLP simplified complicated training process in MindSpore. It supports Trainer and Evaluator interfaces to train and evaluate models easily. MindNLP supports a wide range of NLP tasks, including: * Language modeling * Machine translation * Question answering * Sentiment analysis * Sequence labeling * Summarization MindNLP also supports industry-leading Large Language Models (LLMs), including Llama, GLM, RWKV, etc. For support related to large language models, including pre-training, fine-tuning, and inference demo examples, you can find them in the "llm" directory. To install MindNLP, you can either install it from Pypi, download the daily build wheel, or install it from source. The installation instructions are provided in the documentation. MindNLP is released under the Apache 2.0 license. If you find this project useful in your research, please consider citing the following paper: @misc{mindnlp2022, title={{MindNLP}: a MindSpore NLP library}, author={MindNLP Contributors}, howpublished = {\url{https://github.com/mindlab-ai/mindnlp}}, year={2022} }

OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Its main features include: * Comprehensive support for models and datasets: Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 70+ datasets with about 400,000 questions, comprehensively evaluating the capabilities of the models in five dimensions. * Efficient distributed evaluation: One line command to implement task division and distributed evaluation, completing the full evaluation of billion-scale models in just a few hours. * Diversified evaluation paradigms: Support for zero-shot, few-shot, and chain-of-thought evaluations, combined with standard or dialogue-type prompt templates, to easily stimulate the maximum performance of various models. * Modular design with high extensibility: Want to add new models or datasets, customize an advanced task division strategy, or even support a new cluster management system? Everything about OpenCompass can be easily expanded! * Experiment management and reporting mechanism: Use config files to fully record each experiment, and support real-time reporting of results.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

This repository provides a comprehensive guide to understanding and applying artificial intelligence (AI) theory, including basic knowledge, machine learning, deep learning, and natural language processing (BERT). It features detailed explanations, annotated code, and datasets to help users grasp the concepts and implement them in practice. The repository is continuously updated to ensure the latest information and best practices are covered.

Advanced RAG Techniques is a comprehensive collection of cutting-edge Retrieval-Augmented Generation (RAG) tutorials aimed at enhancing the accuracy, efficiency, and contextual richness of RAG systems. The repository serves as a hub for state-of-the-art RAG enhancements, comprehensive documentation, practical implementation guidelines, and regular updates with the latest advancements. It covers a wide range of techniques from foundational RAG methods to advanced retrieval methods, iterative and adaptive techniques, evaluation processes, explainability and transparency features, and advanced architectures integrating knowledge graphs and recursive processing.

EOLE is an open language modeling toolkit based on PyTorch. It aims to provide a research-friendly approach with a comprehensive yet compact and modular codebase for experimenting with various types of language models. The toolkit includes features such as versatile training and inference, dynamic data transforms, comprehensive large language model support, advanced quantization, efficient finetuning, flexible inference, and tensor parallelism. EOLE is a work in progress with ongoing enhancements in configuration management, command line entry points, reproducible recipes, core API simplification, and plans for further simplification, refactoring, inference server development, additional recipes, documentation enhancement, test coverage improvement, logging enhancements, and broader model support.

AgentLab is an open, easy-to-use, and extensible framework designed to accelerate web agent research. It provides features for developing and evaluating agents on various benchmarks supported by BrowserGym. The framework allows for large-scale parallel agent experiments using ray, building blocks for creating agents over BrowserGym, and a unified LLM API for OpenRouter, OpenAI, Azure, or self-hosted using TGI. AgentLab also offers reproducibility features, a unified LeaderBoard, and supports multiple benchmarks like WebArena, WorkArena, WebLinx, VisualWebArena, AssistantBench, GAIA, Mind2Web-live, and MiniWoB.

TheCodersGig is an AI-powered open-source social network platform for developers, facilitating seamless connection and collaboration. It features an integrated utility marketplace for creating plugins easily, automating backend development with scalable code. The user-friendly interface supports API integration, data models, databases, authentication, and authorization. The platform's architecture includes frontend, backend, AI services, database, marketplace, security, and DevOps layers, enabling customization and diverse integrations. Key components encompass technologies like React.js, Node.js, Python-based AI frameworks, SQL/NoSQL databases, payment gateways, security protocols, and DevOps tools for automation and scalability.

This repository provides a ready-to-run basic Slack AI solution that allows users to summarize threads and channels using OpenAI. Users can generate thread summaries, channel overviews, channel summaries since a specific time, and full channel summaries. The tool is powered by GPT-3.5-Turbo and an ensemble of NLP models. It requires Python 3.8 or higher, an OpenAI API key, Slack App with associated API tokens, Poetry package manager, and ngrok for local development. Users can customize channel and thread summaries, run tests with coverage using pytest, and contribute to the project for future enhancements.

MedicalGPT is a training medical GPT model with ChatGPT training pipeline, implement of Pretraining, Supervised Finetuning, RLHF(Reward Modeling and Reinforcement Learning) and DPO(Direct Preference Optimization).

RAPTOR introduces a novel approach to retrieval-augmented language models by constructing a recursive tree structure from documents. This allows for more efficient and context-aware information retrieval across large texts, addressing common limitations in traditional language models. Users can add documents to the tree, answer questions based on indexed documents, save and load the tree, and extend RAPTOR with custom summarization, question-answering, and embedding models. The tool is designed to be flexible and customizable for various NLP tasks.

This repository contains a collection of AI projects covering various areas of machine learning. Each project is accompanied by detailed articles on the associated blog sciblog. Projects range from introductory topics like Convolutional Neural Networks and Transfer Learning to advanced topics like Fraud Detection and Recommendation Systems. The repository also includes tutorials on data generation, distributed training, natural language processing, and time series forecasting. Additionally, it features visualization projects such as football match visualization using Datashader.

OpenManus is an open-source project aiming to replicate the capabilities of the Manus AI agent, known for autonomously executing complex tasks like travel planning and stock analysis. The project provides a modular, containerized framework using Docker, Python, and JavaScript, allowing developers to build, deploy, and experiment with a multi-agent AI system. Features include collaborative AI agents, Dockerized environment, task execution support, tool integration, modular design, and community-driven development. Users can interact with OpenManus via CLI, API, or web UI, and the project welcomes contributions to enhance its capabilities.

NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.

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.

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

VedAstro is an open-source Vedic astrology tool that provides accurate astrological predictions and data. It offers a user-friendly website, a chat API, an open API, a JavaScript SDK, a Swiss Ephemeris API, and a machine learning table generator. VedAstro is free to use and is constantly being updated with new features and improvements.

Implement specific web applications based on sketches submitted by users

Provides concise GC troubleshooting and method development advice that is easy to implement.

Your proactive virtual CTO, ready to implement requests

Assists in enhancing e-commerce sites for better conversions with tailored, easy-to-implement advice.

Insurance providers collect and process personal health, financial, and property information, making it crucial to implement comprehensive data protection strategies.

Agente de IA especializado em Proteção de Dados

Guides users on Oracle EPM Cloud services and tasks.

Expert in Your ERP software, specializing in White Label contracts and implementation advice.

ISO27001およびISO/IEC 27002のベストプラクティスに精通したアドバイザー　Expert in ISO27001 and ISO/IEC 27002 best practices.

Japanese-first, young GCP expert with AI diagrams.

Consultor especializado em SAP ECC 6

Demystifying ISO 26262: Your Simple Guide to Automotive Functional Safety

Mon expert en protection des données

Spécialiste ISO 15189 et documents COFRAC pour les conseils en qualité des laboratoires médicaux.

Guides organization in telecommunications systems implementation and optimization.

Guides in designing, implementing, and maintaining technical architecture.

Manages credit risk and implements effective collection strategies.

Offering advice and guidance for those managing a Salesforce Center of Excellence

Expert in manufacturing operations and digital transformation guidance

Guides the development and implementation of IT systems architecture.