Best AI tools for< Process Datasets >

Shaip is a human-powered data processing service specializing in AI and ML models. They offer a wide range of services including data collection, annotation, de-identification, and more. Shaip provides high-quality training data for various AI applications, such as healthcare AI, conversational AI, and computer vision. With over 15 years of expertise, Shaip helps organizations unlock critical information from unstructured data, enabling them to achieve better results in their AI initiatives.

Juice Remote GPU is a software that enables AI and Graphics workloads on remote GPUs. It allows users to offload GPU processing for any CUDA or Vulkan application to a remote host running the Juice agent. The software injects CUDA and Vulkan implementations during runtime, eliminating the need for code changes in the application. Juice supports multiple clients connecting to multiple GPUs and multiple clients sharing a single GPU. It is useful for sharing a single GPU across multiple workstations, allocating GPUs dynamically to CPU-only machines, and simplifying development workflows and deployments. Juice Remote GPU performs within 5% of a local GPU when running in the same datacenter. It supports various APIs, including CUDA, Vulkan, DirectX, and OpenGL, and is compatible with PyTorch and TensorFlow. The team behind Juice Remote GPU consists of engineers from Meta, Intel, and the gaming industry.

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.

Future AGI is a revolutionary AI data management platform that aims to achieve 99% accuracy in AI applications across software and hardware. It provides a comprehensive evaluation and optimization platform for enterprises to enhance the performance of their AI models. Future AGI offers features such as creating trustworthy, accurate, and responsible AI, 10x faster processing, generating and managing diverse synthetic datasets, testing and analyzing agentic workflow configurations, assessing agent performance, enhancing LLM application performance, monitoring and protecting applications in production, and evaluating AI across different modalities.

ePlant is an advanced solution for tree care and plant research, offering precision tree monitoring from the lab to the landscape. It provides wireless monitoring solutions with advanced sensors for plant researchers and consulting arborists, enabling efficient data collection and analysis for better decision-making. The platform empowers users to track plant growth, water stress, tree lean, and sway through innovative sensors and data visualization tools. ePlant aims to simplify data management and transform complex datasets into actionable insights for users in the field of plant science and arboriculture.

Synthace is a software and expertise platform designed for Discovery Biology Teams to streamline and optimize their experiments in assay development, media optimization, and purification process development. The platform offers software solutions, training, and on-site support from specialists to help scientists conduct experiments more efficiently and effectively. By leveraging multifactorial methods and automation, Synthace aims to accelerate drug discovery processes and deliver faster, definitive results.

Innovatiana is a data labeling outsourcing platform that offers high-quality datasets for artificial intelligence models. They specialize in image, audio/video, and text data labeling tasks, providing ethical outsourcing with a focus on impact and transparency. Innovatiana recruits and trains their own team in Madagascar, ensuring fair pay and good working conditions. They offer competitive rates, secure data handling, and high-quality labeled data to feed AI models. The platform supports various AI tasks such as Computer Vision, Data Collection, Data Moderation, Documents Processing, and Natural Language Processing.

Sapien.io is a decentralized data foundry that offers data labeling services powered by a decentralized workforce and gamified platform. The platform provides high-quality training data for large language models through a human-in-the-loop labeling process, enabling fine-tuning of datasets to build performant AI models. Sapien combines AI and human intelligence to collect and annotate various data types for any model, offering customized data collection and labeling models across industries.

dataset.macgence is an AI-powered data analysis tool that helps users extract valuable insights from their datasets. It offers a user-friendly interface for uploading, cleaning, and analyzing data, making it suitable for both beginners and experienced data analysts. With advanced algorithms and visualization capabilities, dataset.macgence enables users to uncover patterns, trends, and correlations in their data, leading to informed decision-making. Whether you're a business professional, researcher, or student, dataset.macgence can streamline your data analysis process and enhance your data-driven strategies.

Ai Drawing Generator is a free online tool that revolutionizes drawing generation with AI. It introduces ControlNet, a neural network structure designed to enhance pretrained large diffusion models by incorporating additional input conditions. The tool enables users to convert scribbled drawings into detailed images through deep learning algorithms. It is adaptable for training on personal devices and can handle large datasets ranging from millions to billions. Ai Drawing Generator provides experimental compatibility with various diffusion models, offering users flexibility in choosing models based on their specific needs and preferences.

Pulan is a comprehensive platform designed to assist in collecting, curating, annotating, and evaluating data points for various AI initiatives. It offers services in Natural Language Processing, Data Annotation, and Computer Vision across multiple industries such as Agriculture, Medical, Life Sciences, Government, Automotive, Insurance & Finance, Logistics, Software & Internet, Manufacturing, Retail, Construction, Energy, and Food & Beverage. Pulan provides a one-stop destination for reliable data collection and curation by industry experts, with a vast inventory of millions of datasets available for licensing at a fraction of the cost of creating the data oneself.

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.

Kanaries is an augmented analytics platform that uses AI to automate the process of data exploration and visualization. It offers a variety of features to help users quickly and easily find insights in their data, including: * **RATH:** An AI-powered engine that can automatically generate insights and recommendations based on your data. * **Graphic Walker:** A visual analytics tool that allows you to explore your data in a variety of ways, including charts, graphs, and maps. * **Data Painter:** A data cleaning and transformation tool that makes it easy to prepare your data for analysis. * **Causal Analysis:** A tool that helps you identify and understand the causal relationships between variables in your data. Kanaries is designed to be easy to use, even for users with no prior experience with data analysis. It is also highly scalable, so it can be used to analyze large datasets. Kanaries is a valuable tool for anyone who wants to quickly and easily find insights in their data. It can be used by businesses of all sizes, and it is particularly well-suited for organizations that are looking to improve their data-driven decision-making.

Generative Aid Data Scientist is an AI tool designed to assist data scientists in generating insights and analysis from complex datasets. It utilizes advanced algorithms and machine learning techniques to provide valuable recommendations and predictions for data-driven decision-making. The tool offers a user-friendly interface that allows data scientists to input their data and receive actionable results in a timely manner. With its powerful capabilities, Generative Aid Data Scientist streamlines the data analysis process and enhances the efficiency of data-driven projects.

Trazable LifeCycle is a sustainability software designed to measure, improve, and report the sustainability of companies. It simplifies the process of measuring and reporting environmental impact by providing tools to create process maps, add environmental impact data, and generate key sustainability indicators. The software is tailored for the food industry, offering over 50 million industry-specific data points to aid in decision-making and compliance with sustainability regulations. Trazable LifeCycle ensures data validity by using constantly updated and validated datasets, allowing users to measure both product and organizational carbon footprints.

Patee.io is an AI-powered platform that helps businesses automate their data annotation and labeling tasks. With Patee.io, businesses can easily create, manage, and annotate large datasets, which can then be used to train machine learning models. Patee.io offers a variety of features that make it easy to annotate data, including a user-friendly interface, a variety of annotation tools, and the ability to collaborate with others. Patee.io also offers a number of pre-built models that can be used to automate the annotation process, saving businesses time and money.

Appen is a leading provider of high-quality data for training AI models. The company's end-to-end platform, flexible services, and deep expertise ensure the delivery of high-quality, diverse data that is crucial for building foundation models and enterprise-ready AI applications. Appen has been providing high-quality datasets that power the world's leading AI models for decades. The company's services enable it to prepare data at scale, meeting the demands of even the most ambitious AI projects. Appen also provides enterprises with software to collect, curate, fine-tune, and monitor traditionally human-driven tasks, creating massive efficiencies through a trustworthy, traceable process.

Weavel is an AI tool designed to revolutionize prompt engineering for large language models (LLMs). It offers features such as tracing, dataset curation, batch testing, and evaluations to enhance the performance of LLM applications. Weavel enables users to continuously optimize prompts using real-world data, prevent performance regression with CI/CD integration, and engage in human-in-the-loop interactions for scoring and feedback. Ape, the AI prompt engineer, outperforms competitors on benchmark tests and ensures seamless integration and continuous improvement specific to each user's use case. With Weavel, users can effortlessly evaluate LLM applications without the need for pre-existing datasets, streamlining the assessment process and enhancing overall performance.

Aitodata.com is an AI-powered data analysis platform that empowers users to extract valuable insights from their data effortlessly. The platform offers a user-friendly interface and advanced algorithms to help users analyze, visualize, and interpret data in a meaningful way. With Aitodata.com, users can streamline their data analysis process, make data-driven decisions, and uncover hidden patterns and trends within their datasets.

Navalai.co is an AI-powered tool that offers advanced solutions for data analysis and decision-making. It utilizes cutting-edge artificial intelligence algorithms to provide users with valuable insights and predictions based on complex data sets. The platform is designed to streamline the process of data analysis and help users make informed decisions quickly and efficiently. With its user-friendly interface and powerful features, Navalai.co is a valuable tool for businesses and individuals looking to leverage AI technology for data-driven decision-making.

This repository contains the source code for the SIGIR 2023 paper 'Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited'. It provides resources for evaluating foundation, transferable, multi-modal, and LLM recommendation models, along with datasets, pre-trained models, and training strategies for IDRec and MoRec using in-batch debiased cross-entropy loss. The repository also offers large-scale datasets, code for SASRec with in-batch debias cross-entropy loss, and information on joining the lab for research opportunities.

This repository contains the code for the paper 'Towards Economical Inference: Enabling DeepSeek's Multi-Head Latent Attention in Any Transformer-based LLMs'. It provides tools for fine-tuning and evaluating Llama models, converting models between different frameworks, processing datasets, and performing specific model training tasks like Partial-RoPE Fine-Tuning and Multiple-Head Latent Attention Fine-Tuning. The repository also includes commands for model evaluation using Lighteval and LongBench, along with necessary environment setup instructions.

LLMsForTimeSeries is a repository that questions the usefulness of language models in time series forecasting. The work shows that simple baselines outperform most language model-based time series forecasting models. It includes ablation studies on LLM-based TSF methods and introduces the PAttn method, showcasing the performance of patching and attention structures in forecasting. The repository provides datasets, setup instructions, and scripts for running ablations on different datasets.

Deeppowers is a powerful Python library for deep learning applications. It provides a wide range of tools and utilities to simplify the process of building and training deep neural networks. With Deeppowers, users can easily create complex neural network architectures, perform efficient training and optimization, and deploy models for various tasks. The library is designed to be user-friendly and flexible, making it suitable for both beginners and experienced deep learning practitioners.

Wandbot is a question-answering bot designed for Weights & Biases documentation. It employs Retrieval Augmented Generation with a ChromaDB backend for efficient responses. The bot features periodic data ingestion, integration with Discord and Slack, and performance monitoring through logging. It has a fallback mechanism for model selection and is evaluated based on retrieval accuracy and model-generated responses. The implementation includes creating document embeddings, constructing the Q&A RAGPipeline, model selection, deployment on FastAPI, Discord, and Slack, logging and analysis with Weights & Biases Tables, and performance evaluation.

LLaMa2lang is a repository containing convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language that isn't English. The repository aims to improve the performance of LLaMa3 for non-English languages by combining fine-tuning with RAG. Users can translate datasets, extract threads, turn threads into prompts, and finetune models using QLoRA and PEFT. Additionally, the repository supports translation models like OPUS, M2M, MADLAD, and base datasets like OASST1 and OASST2. The process involves loading datasets, translating them, combining checkpoints, and running inference using the newly trained model. The repository also provides benchmarking scripts to choose the right translation model for a target language.

NVIDIA Generative AI Examples are state-of-the-art examples that are easy to deploy, test, and extend. All examples run on the high performance NVIDIA CUDA-X software stack and NVIDIA GPUs. These examples showcase the capabilities of NVIDIA's Generative AI platform, which includes tools, frameworks, and models for building and deploying generative AI applications.

Moonshot is a simple and modular tool developed by the AI Verify Foundation to evaluate Language Model Models (LLMs) and LLM applications. It brings Benchmarking and Red-Teaming together to assist AI developers, compliance teams, and AI system owners in assessing LLM performance. Moonshot can be accessed through various interfaces including User-friendly Web UI, Interactive Command Line Interface, and seamless integration into MLOps workflows via Library APIs or Web APIs. It offers features like benchmarking LLMs from popular model providers, running relevant tests, creating custom cookbooks and recipes, and automating Red Teaming to identify vulnerabilities in AI systems.

Easy Dataset is a specialized application designed to streamline the creation of fine-tuning datasets for Large Language Models (LLMs). It offers an intuitive interface for uploading domain-specific files, intelligently splitting content, generating questions, and producing high-quality training data for model fine-tuning. With Easy Dataset, users can transform domain knowledge into structured datasets compatible with all OpenAI-format compatible LLM APIs, making the fine-tuning process accessible and efficient.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

FiftyOne is an open-source tool designed for building high-quality datasets and computer vision models. It supercharges machine learning workflows by enabling users to visualize datasets, interpret models faster, and improve efficiency. With FiftyOne, users can explore scenarios, identify failure modes, visualize complex labels, evaluate models, find annotation mistakes, and much more. The tool aims to streamline the process of improving machine learning models by providing a comprehensive set of features for data analysis and model interpretation.

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

This repository focuses on organizing resources for building synthetic datasets using large language models. It covers important datasets, libraries, tools, tutorials, and papers related to synthetic data generation. The goal is to provide pragmatic and practical resources for individuals interested in creating synthetic datasets for machine learning applications.

Autolabel is a Python library designed to label, clean, and enrich text datasets using Large Language Models (LLMs). It provides a simple 3-step process for labeling data, supports various NLP tasks, and offers features like confidence estimation, explanations, and state management. Users can access Refuel hosted LLMs for labeling and confidence estimation, and the library supports commercial and open source LLMs from providers like OpenAI, Anthropic, HuggingFace, and Google. Autolabel aims to streamline the labeling process for machine learning tasks by leveraging state-of-the-art LLM techniques and minimizing costs and experimentation time.

Lance is a modern columnar data format optimized for ML workflows and datasets. It offers high-performance random access, vector search, zero-copy automatic versioning, and ecosystem integrations with Apache Arrow, Pandas, Polars, and DuckDB. Lance is designed to address the challenges of the ML development cycle, providing a unified data format for collection, exploration, analytics, feature engineering, training, evaluation, deployment, and monitoring. It aims to reduce data silos and streamline the ML development process.

The End-to-End LLM Bootcamp is a comprehensive training program that covers the entire process of developing and deploying large language models. Participants learn to preprocess datasets, train models, optimize performance using NVIDIA technologies, understand guardrail prompts, and deploy AI pipelines using Triton Inference Server. The bootcamp includes labs, challenges, and practical applications, with a total duration of approximately 7.5 hours. It is designed for individuals interested in working with advanced language models and AI technologies.

This repository is a curated list of awesome public object detection and recognition datasets. It includes a wide range of datasets related to object detection and recognition tasks, such as general detection and recognition datasets, autonomous driving datasets, adverse weather datasets, person detection datasets, anti-UAV datasets, optical aerial imagery datasets, low-light image datasets, infrared image datasets, SAR image datasets, multispectral image datasets, 3D object detection datasets, vehicle-to-everything field datasets, super-resolution field datasets, and face detection and recognition datasets. The repository also provides information on tools for data annotation, data augmentation, and data management related to object detection tasks.

qapyq is an image viewer and AI-assisted editing tool designed to help curate datasets for generative AI models. It offers features such as image viewing, editing, captioning, batch processing, and AI assistance. Users can perform tasks like cropping, scaling, editing masks, tagging, and applying sorting and filtering rules. The tool supports state-of-the-art captioning and masking models, with options for model settings, GPU acceleration, and quantization. qapyq aims to streamline the process of preparing images for training AI models by providing a user-friendly interface and advanced functionalities.

Upload your process map and I will analyse and suggest improvements

Friendly process engineer for Coda.io

Guides clear BPMN process design with ASCII art

Optimizes production processes for improved efficiency and quality.

Optimizes business operations through process enhancements.

Optimizes production processes for efficient large-scale operations.

Improves operational efficiency by optimizing processes and reducing waste.

Discover Process Talks: Your Next Investment!

Optimizes manufacturing processes for efficiency and quality.

Emulating Whitehead's insights on 'Process and Reality'

Process Documentation for serving GPTs.

Trademark Process Assistant, Not an Attorney & Definitely Not Legal Advice (independently verify info received). Gain insights on U.S. trademark process & concepts, USPTO resources, application steps & more - all while being reminded of the importance of consulting legal pros 4 specific guidance.

Structured process for prioritizing marketing tasks based on strategic alignment. Outputs in Eisenhower, RACI and other methodologies.

Assists in the caregiving process for seniors.

Guides future parents through the adoption process with empathy and information.

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

Formal SBIR process expert for Air Force/Space Force

To streamline the process of creating scripts for Brut-style videos by providing structured guidance in researching, strategizing, and writing, ensuring the final script is rich in content and visually captivating.

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I will give you all the information about the Audit and Certification process of ISO 9001 Management Systems, either in the form of a specialization course or consultations.