Best AI tools for< Prepare Data For Training >

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.

O'Reilly Media is an AI-powered platform offering technology and business training for individuals, businesses, government, and higher education institutions. With over 5,000 companies relying on their digital courses, O'Reilly provides resources to upskill teams in tools and technologies driving business outcomes. The platform features courses, certifications, interactive learning, live events, and insights reporting. O'Reilly leverages generative AI tools and large language models to help employees stay ahead in their tech careers. The platform also offers diversity scholarships and awards to promote inclusivity and recognize excellence in technical learning. With a history of over 40 years, O'Reilly has been sharing knowledge through books, tech conferences, and online learning content.

Kona is an AI-powered platform designed to provide real-time coaching and support to managers in remote organizations. It offers personalized coaching, meeting assistance, leadership advice, and performance review preparation. Kona helps managers save time, improve leadership skills, and enhance team effectiveness by leveraging AI technology. The platform is built to reinforce and scale manager training content, provide data analytics insights, and integrate with existing tools to support better feedback and prioritization. Kona is designed to ensure every manager leads according to the organization's best practices and offers a secure and confidential environment for coaching and support.

Intuition Machines is a leading provider of Privacy-Preserving AI/ML platforms and research solutions. They offer products and services that cater to category leaders worldwide, focusing on AI/ML research, security, and risk analysis. Their innovative solutions help enterprises prepare for the future by leveraging AI for a wide range of problems. With a strong emphasis on privacy and security, Intuition Machines is at the forefront of developing cutting-edge AI technologies.

Saasguru is a comprehensive Salesforce skilling and certification platform that empowers individuals to launch or advance their Salesforce careers. It offers a wide range of learning resources, including live classes, mock exams, projects, and personalized mentorship, to help learners develop a strong foundation in Salesforce and prepare for certification exams. Saasguru also provides job readiness support, connecting learners with potential employers and providing interview preparation assistance.

Ren is an AI-powered leadership coaching platform that offers personalized coaching to employees at all levels within an organization. It leverages advanced AI technology and decades of human coaching experience to provide real-time guidance, feedback, and support in alignment with company values and goals. Ren is scalable, private, and secure, enabling individuals to tackle tough conversations, align with their teams, and foster personal growth based on individualized data profiles. The platform also provides organizational dashboards for unique insights while preserving employee privacy.

nuvo is an AI-powered data import solution that offers fast, secure, and scalable data import solutions for software companies. It provides tools like nuvo Data Importer SDK and nuvo Data Pipeline to streamline manual and recurring ETL data imports, enabling users to manage data imports independently. With AI-enhanced automation, nuvo helps prepare clean data for preferred systems quickly and efficiently, reducing manual effort and improving data quality. The platform allows users to upload unlimited data in various formats, match imported data to system schemas, clean and validate data, and import clean data into target systems with just a click.

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.

Akkio is an AI data platform designed specifically for agencies and their clients. It offers a range of features to help agencies improve performance, including data preparation, predictive analytics, and reporting. Akkio is easy to use, with a drag-and-drop interface and no coding required. It also integrates with a variety of data sources, making it easy to get started.

Trifacta API Documentation provides reference information on all of the available endpoints for each product edition. This website does not factor disabled features or your specific account permissions. To review API documentation for the endpoints to which your account has access, please select Help menu > API Documentation from the Trifacta application menu.

Tellius is an AI Augmented Analytics Software and Decision Intelligence platform that empowers users to get faster insights from data, break silos between Business Intelligence (BI) and AI, and accelerate complex data analysis with AI-driven automation. The platform offers guided insights, data preparation, natural language search, automated machine learning, and self-service analytics & reporting. Tellius is loved by analytics and business teams for providing instant ad hoc answers, simplifying complex analysis, and surfacing hidden key drivers and anomalies through best-in-class automated insights.

SEOlligence is an AI-powered tool designed for e-commerce businesses to optimize product titles, subtitles, descriptions, and meta data for better search rankings and increased online visibility. It offers a range of services including SEO optimization, product title and description enhancement, keyword research, FAQ schema optimization, and meta title and description optimization. With the power of Artificial Intelligence, SEOlligence empowers businesses to improve their search rankings, drive organic traffic, and attract more customers. The tool is compatible with all e-commerce platforms and provides fast, accurate, and cost-effective solutions for localization and SEO optimization.

Firecrawl is an advanced web crawling and data conversion tool designed to transform any website into clean, LLM-ready markdown. It automates the collection, cleaning, and formatting of web data, streamlining the preparation process for Large Language Model (LLM) applications. Firecrawl is best suited for business websites, documentation, and help centers, offering features like crawling all accessible subpages, handling dynamic content, converting data into well-formatted markdown, and more. It is built by LLM engineers for LLM engineers, providing clean data the way users want it.

GetFlashInsights is a website that provides valuable insights and analytics for businesses and individuals. It offers a range of tools and features to help users analyze data, track performance, and make informed decisions. With a user-friendly interface and powerful capabilities, GetFlashInsights is a go-to platform for data-driven decision-making.

Sku Fetch is a powerful tool that helps you fetch, prepare, and list product information from hundreds of suppliers. It provides multiple free templates, helps you find keywords, and can even add UPCs to your products. With Sku Fetch, you can also analyze your competition, add reviews to your listings, and process multiple products with preset settings. Plus, it supports multiple listers, such as Wise Lister, Crazy Lister, eBay Selling Manager, Ink Frog, Shopify, and others.

Alteryx offers a leading AI Platform for Enterprise Analytics that delivers actionable insights by automating analytics. The platform combines the power of data preparation, analytics, and machine learning to help businesses make better decisions faster. With Alteryx, businesses can connect to a wide variety of data sources, prepare and clean data, perform advanced analytics, and build and deploy machine learning models. The platform is designed to be easy to use, even for non-technical users, and it can be deployed on-premises or in the cloud.

Labellerr is a data labeling software that helps AI teams prepare high-quality labels 99 times faster for Vision, NLP, and LLM models. The platform offers automated annotation, advanced analytics, and smart QA to process millions of images and thousands of hours of videos in just a few weeks. Labellerr's powerful analytics provides full control over output quality and project management, making it a valuable tool for AI labeling partners.

The website offers an AI-powered tool that allows users to easily convert images into fully editable PowerPoint slides. By leveraging the capabilities of GPT-4o, the tool eliminates the need for manual data copying, saving users valuable time and effort. With a user-friendly interface and high-quality output, users can quickly create professional presentations without the hassle of traditional methods.

PrepMasterAI is an AI-powered platform designed to help individuals ace their job interviews by providing personalized practice questions, real-time feedback, and performance tracking. Users can unlock their full potential through tailored practice questions and insights to improve their interview skills. The platform aims to assist job seekers in identifying and enhancing their strengths and weaknesses to increase their chances of landing their dream job.

InterviewAI is an AI-powered platform that helps users prepare for and practice their job interviews. It offers a range of features, including practice interviews with AI, personalized cover letter generation, and feedback on interview performance. InterviewAI is designed to help users improve their interview skills, increase their confidence, and succeed in their job search.

This repository contains the code for the paper 'LESS: Selecting Influential Data for Targeted Instruction Tuning'. The work proposes a data selection method to choose influential data for inducing a target capability. It includes steps for warmup training, building the gradient datastore, selecting data for a task, and training with the selected data. The repository provides tools for data preparation, data selection pipeline, and evaluation of the model trained on the selected data.

MaskLLM is a learnable pruning method that establishes Semi-structured Sparsity in Large Language Models (LLMs) to reduce computational overhead during inference. It is scalable and benefits from larger training datasets. The tool provides examples for running MaskLLM with Megatron-LM, preparing LLaMA checkpoints, pre-tokenizing C4 data for Megatron, generating prior masks, training MaskLLM, and evaluating the model. It also includes instructions for exporting sparse models to Huggingface.

ChatSim is a tool designed for editable scene simulation for autonomous driving via LLM-Agent collaboration. It provides functionalities for setting up the environment, installing necessary dependencies like McNeRF and Inpainting tools, and preparing data for simulation. Users can train models, simulate scenes, and track trajectories for smoother and more realistic results. The tool integrates with Blender software and offers options for training McNeRF models and McLight's skydome estimation network. It also includes a trajectory tracking module for improved trajectory tracking. ChatSim aims to facilitate the simulation of autonomous driving scenarios with collaborative LLM-Agents.

Groma is a grounded multimodal assistant that excels in region understanding and visual grounding. It can process user-defined region inputs and generate contextually grounded long-form responses. The tool presents a unique paradigm for multimodal large language models, focusing on visual tokenization for localization. Groma achieves state-of-the-art performance in referring expression comprehension benchmarks. The tool provides pretrained model weights and instructions for data preparation, training, inference, and evaluation. Users can customize training by starting from intermediate checkpoints. Groma is designed to handle tasks related to detection pretraining, alignment pretraining, instruction finetuning, instruction following, and more.

Recommenders is a project under the Linux Foundation of AI and Data that assists researchers, developers, and enthusiasts in prototyping, experimenting with, and bringing to production a range of classic and state-of-the-art recommendation systems. The repository contains examples and best practices for building recommendation systems, provided as Jupyter notebooks. It covers tasks such as preparing data, building models using various recommendation algorithms, evaluating algorithms, tuning hyperparameters, and operationalizing models in a production environment on Azure. The project provides utilities to support common tasks like loading datasets, evaluating model outputs, and splitting training/test data. It includes implementations of state-of-the-art algorithms for self-study and customization in applications.

Apollo is a multilingual medical LLM that covers English, Chinese, French, Hindi, Spanish, Hindi, and Arabic. It is designed to democratize medical AI to 6B people. Apollo has achieved state-of-the-art results on a variety of medical NLP tasks, including question answering, medical dialogue generation, and medical text classification. Apollo is easy to use and can be integrated into a variety of applications, making it a valuable tool for healthcare professionals and researchers.

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.

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.

SoM-LLaVA is a new data source and learning paradigm for Multimodal LLMs, empowering open-source Multimodal LLMs with Set-of-Mark prompting and improved visual reasoning ability. The repository provides a new dataset that is complementary to existing training sources, enhancing multimodal LLMs with Set-of-Mark prompting and improved general capacity. By adding 30k SoM data to the visual instruction tuning stage of LLaVA, the tool achieves 1% to 6% relative improvements on all benchmarks. Users can train SoM-LLaVA via command line and utilize the implementation to annotate COCO images with SoM. Additionally, the tool can be loaded in Huggingface for further usage.

The 'gritlm' repository provides all materials for the paper Generative Representational Instruction Tuning. It includes code for inference, training, evaluation, and known issues related to the GritLM model. The repository also offers models for embedding and generation tasks, along with instructions on how to train and evaluate the models. Additionally, it contains visualizations, acknowledgements, and a citation for referencing the work.

RWKV is an RNN with Transformer-level LLM performance, which can also be directly trained like a GPT transformer (parallelizable). And it's 100% attention-free. You only need the hidden state at position t to compute the state at position t+1. You can use the "GPT" mode to quickly compute the hidden state for the "RNN" mode. So it's combining the best of RNN and transformer - **great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding** (using the final hidden state).

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

This repository contains the code to prepare the data for the Amber 7B language model. The final training data comes from three sources: RedPajama V1, RefinedWeb, and StarCoderData. The data preparation involves downloading untokenized data, tokenizing the data using the Huggingface tokenizer, concatenating tokens into 2048 token sequences, merging datasets, and splitting the merged dataset into 360 chunks. Each tokenized data chunk is a jsonl file containing samples with 2049 tokens. The repository provides scripts for downloading datasets, tokenizing and concatenating sequences, validating data, and merging subsets into chunks.

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

FarmVibes.AI is a repository focused on developing multi-modal geospatial machine learning models for agriculture and sustainability. It enables users to fuse various geospatial and spatiotemporal datasets, such as satellite imagery, drone imagery, and weather data, to generate robust insights for agriculture-related problems. The repository provides fusion workflows, data preparation tools, model training notebooks, and an inference engine to facilitate the creation of geospatial models tailored for agriculture and farming. Users can interact with the tools via a local cluster, REST API, or a Python client, and the repository includes documentation and notebook examples to guide users in utilizing FarmVibes.AI for tasks like harvest date detection, climate impact estimation, micro climate prediction, and crop identification.

This repository contains custom recipes for H2O Driverless AI, which is an Automatic Machine Learning platform for the Enterprise. Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime to automate feature engineering, model building, visualization, and interpretability. Users can gain control over the optimization choices made by Driverless AI by providing their own custom recipes. The repository includes recipes for various tasks such as data manipulation, data preprocessing, feature selection, data augmentation, model building, scoring, and more. Best practices for creating and using recipes are also provided, including security considerations, performance tips, and safety measures.

ReST-MCTS is a reinforced self-training approach that integrates process reward guidance with tree search MCTS to collect higher-quality reasoning traces and per-step value for training policy and reward models. It eliminates the need for manual per-step annotation by estimating the probability of steps leading to correct answers. The inferred rewards refine the process reward model and aid in selecting high-quality traces for policy model self-training.

RLAIF-V is a novel framework that aligns MLLMs in a fully open-source paradigm for super GPT-4V trustworthiness. It maximally exploits open-source feedback from high-quality feedback data and online feedback learning algorithm. Notable features include achieving super GPT-4V trustworthiness in both generative and discriminative tasks, using high-quality generalizable feedback data to reduce hallucination of different MLLMs, and exhibiting better learning efficiency and higher performance through iterative alignment.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

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