Best AI tools for< Present Data >

ExcelDashboard Ai is an AI tool that allows users to instantly convert Excel data into interactive dashboards. The tool simplifies the process of creating visually appealing and insightful dashboards without the need for complex coding or design skills. Users can easily upload their Excel files, customize the dashboard layout, and visualize data in a user-friendly format. ExcelDashboard Ai streamlines the dashboard creation process, saving time and effort for individuals and businesses looking to present data in a more engaging way.

ChartPixel is an AI-assisted data analysis platform that empowers users to effortlessly generate charts, insights, and actionable statistics in just 30 seconds. The platform is designed to demystify data and analysis, making it accessible to users of all skill levels. ChartPixel combines the power of AI with domain expertise to provide secure and reliable output, ensuring trustworthy results without compromising data privacy. With user-friendly features and educational tools, ChartPixel helps users clean, wrangle, visualize, and present data with ease, catering to both beginners and professionals.

ChartAI is an AI-powered tool that helps you create beautiful charts and graphs from your data in seconds. With ChartAI, you can easily create bar charts, line charts, pie charts, and more. You can also customize your charts with different colors, fonts, and styles. ChartAI is the perfect tool for anyone who wants to create professional-looking charts and graphs quickly and easily.

Kroma is an AI-powered platform that offers expert PowerPoint slides for businesses and startups. It provides smart templates, AI features, and expert content to help users create persuasive pitches, showcase ideas, present data, and propose B2B services. With Kroma, users can easily create eye-catching charts and graphs, access a wide range of creative assets, and utilize data visualization tools to enhance their presentations.

Columns is an AI tool designed to automate data storytelling. It helps users in creating compelling narratives and visualizations from their data without the need for manual intervention. With Columns, users can easily transform raw data into engaging stories, making data analysis more accessible and impactful. The tool offers a user-friendly interface and a range of customization options to tailor the storytelling process to individual needs.

DMLR (Data-centric Machine Learning Research) is an AI tool that focuses on advancing research in data-centric machine learning. It organizes workshops, research retreats, maintains a journal, and runs a working group to support infrastructure projects. The platform covers topics such as data collection, governance, bias, and drifts, as well as data-centric explainable AI and AI alignment. DMLR encourages submissions around the theme of AI for Science, using AI to tackle scientific challenges and accelerate discoveries.

JobXRecruiter is an AI-powered CV review tool designed for recruiters to streamline the candidate evaluation process. It automates the review of resumes, provides detailed candidate analysis, and helps recruiters save time by focusing on hiring rather than manual screening. The tool offers a 1-minute setup, reduces candidate evaluation time, and eliminates tedious screening tasks. With JobXRecruiter, recruiters can create projects for each vacancy, receive match scores for candidates, and easily shortlist the best candidates without opening individual CVs. The application is secure, efficient, and a game-changer for recruiters looking to optimize their hiring process.

Preps is an AI-powered mock interview simulation platform designed to help users prepare for technical interviews. It offers realistic interview scenarios that mimic real-world technical interviews conducted at top tech companies. Users can practice with AI interviewers in real-time, receive personalized feedback, and improve their interview skills. With Preps, users can simulate various interview scenarios, practice unexpected questions, and refine their answers to increase their chances of success in technical interviews.

TWIML is a platform that provides intelligent content focusing on Machine Learning and Artificial Intelligence technologies. It offers podcasts, articles, and resources to practitioners, innovators, and leaders, giving insights into the present and future of ML & AI. The platform covers a wide range of topics such as deep reinforcement learning, fusion energy production, data-centric AI, responsible AI, and machine learning platform strategies.

Briefly is an AI application that provides AI meeting summaries, insights, and follow-ups. It offers features such as automatic call transcriptions, AI summaries, CRM integration, personalized health scores, and dynamic account plans. Briefly helps users streamline communication, enhance productivity, and optimize customer engagement effortlessly.

Creators is a website that offers a service to create pitch decks for startups and growing businesses. They specialize in creating visually stunning and impactful pitch decks that tell the story of the business and capture the attention of investors. They use a data-driven approach to storytelling, incorporating relevant data and analytics to back up the idea and prove its potential to investors. They also use artificial intelligence to identify the most compelling way to present the information, ensuring that the pitch deck is not just informative, but also engaging. Creators has a team of expert designers who excel at transforming complex ideas into clear, understandable visuals that are both stunning and highly effective in communicating the message to potential investors.

Prezent is a business communication and presentation productivity platform that uses AI to help users create, transform, enable, and learn. With Prezent, users can access a library of 35,000+ slides, 100+ expert-curated storylines, and a variety of tools to generate personalized presentations, convert slides into different templates, and add designer-quality polish. Prezent also offers a range of learning resources, including bite-sized learning modules, interactive tools, and access to communication experts. The platform is trusted by Fortune 2000 companies and has been featured in publications such as Forbes, The Wall Street Journal, and TechCrunch.

Gift Wizard is an AI-powered gift suggestion tool that helps users find the perfect gift for any occasion or recipient. By answering a few simple questions about the recipient, the tool's intelligent algorithm provides personalized gift ideas tailored to their preferences. It is easy to use, offers thoughtful and relevant gift ideas, and is powered by AI technology. Gift Wizard is free for everyone, does not require sign-up, and provides real-time product data to enhance the gift-giving experience.

MindpoolAI is a tool that allows users to access multiple leading AI models with a single query. This means that users can get the answers they are looking for, spark ideas, and fuel their work, creativity, and curiosity. MindpoolAI is easy to use and does not require any technical expertise. Users simply need to enter their prompt and select the AI models they want to compare. MindpoolAI will then send the query to the selected models and present the results in an easy-to-understand format.

PerfectGift.AI is an AI-powered gift ideas generator that helps you find the perfect gift for any occasion. With a database of over 10,000 gifts, PerfectGift.AI can help you find the perfect gift for anyone, regardless of their age, interests, or budget.

AFFiNE is an all-in-one KnowledgeOS platform that integrates documents, whiteboards, and databases with AI capabilities. It offers a workspace for writing, drawing, and planning, allowing users to enhance creativity and productivity. The platform is privacy-focused, user-centric, and open-source, catering to individuals, startups, and established organizations. AFFiNE aims to streamline workflows, foster collaboration, and provide a vibrant community space for users to connect and inspire each other.

Personal AI is a unique AI model that represents who you truly are. It is trained on your personal memory and is private to you. With Personal AI, you can always be there for yourself, even when you're not physically present. You can use Personal AI to chat with yourself, get advice, or simply reflect on your thoughts and feelings. Personal AI is the perfect way to get to know yourself better and reach your full potential.

Dan Rose AI is a platform focused on applied artificial intelligence, providing insights and strategies on how AI can be utilized in the present time for real value. The website features blog posts, speaking engagements, and consulting services related to AI applications and strategies. Dan Rose Johansen, the founder, emphasizes practical approaches to AI implementation and its strategic use.

Iris Dating is an AI dating application that leverages artificial intelligence to match and date online. The app uses AI to understand users' preferences and present them with matches based on mutual attraction. By decoding the science of attraction, Iris Dating aims to revolutionize online dating by providing users with more meaningful and successful relationships.

GoAudience is a custom audience platform that leverages AI to help brands find new customers based on their credit card spending history. It integrates easily with Meta and is effective across all categories. The platform offers features such as AI-powered audience creation, real-time consumer spending data, plug-and-play simplicity, enterprise precision at SMB pricing, and the ability to pause subscriptions anytime. GoAudience enables users to create top-performing custom audiences, track performance, measure ROI, and present results easily. It aims to provide targeting that is always on target by building custom audience lists from real-time consumer spending data. The platform prioritizes user privacy by securely transmitting data and deleting raw data after transmission.

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.

Lightning Lab is a public template for artificial intelligence and machine learning research projects using Lightning AI's PyTorch Lightning. It provides a structured project layout with modules for command line interface, experiment utilities, Lightning Module and Trainer, data acquisition and preprocessing, model serving APIs, project configurations, training checkpoints, technical documentation, logs, notebooks for data analysis, requirements management, testing, and packaging. The template simplifies the setup of deep learning projects and offers extras for different domains like vision, text, audio, reinforcement learning, and forecasting.

The vscode-dbt-power-user is an open-source extension that enhances the functionality of Visual Studio Code to seamlessly work with dbt™. It provides features such as auto-complete for dbt™ code, previewing query results, column lineage visualization, generating dbt™ models, documentation generation, deferring model builds, running parent/child models and tests with a click, compiled query preview and explanation, project health check, SQL validation, BigQuery cost estimation, and other features like dbt™ logs viewer. The extension is fully compatible with dev containers, code spaces, and remote extensions, supporting dbt™ versions above 1.0.

Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Deep Lake can be used for: 1. Storing data and vectors while building LLM applications 2. Managing datasets while training deep learning models Deep Lake simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in your own cloud and in one place. Deep Lake is used by Intel, Bayer Radiology, Matterport, ZERO Systems, Red Cross, Yale, & Oxford.

LLM Finetuning toolkit is a config-based CLI tool for launching a series of LLM fine-tuning experiments on your data and gathering their results. It allows users to control all elements of a typical experimentation pipeline - prompts, open-source LLMs, optimization strategy, and LLM testing - through a single YAML configuration file. The toolkit supports basic, intermediate, and advanced usage scenarios, enabling users to run custom experiments, conduct ablation studies, and automate fine-tuning workflows. It provides features for data ingestion, model definition, training, inference, quality assurance, and artifact outputs, making it a comprehensive tool for fine-tuning large language 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.

Reflection-Tuning is a project focused on improving the quality of instruction-tuning data through a reflection-based method. It introduces Selective Reflection-Tuning, where the student model can decide whether to accept the improvements made by the teacher model. The project aims to generate high-quality instruction-response pairs by defining specific criteria for the oracle model to follow and respond to. It also evaluates the efficacy and relevance of instruction-response pairs using the r-IFD metric. The project provides code for reflection and selection processes, along with data and model weights for both V1 and V2 methods.

The Microsoft AI for Earth program hosts geospatial data on Azure that is important to environmental sustainability and Earth science. This repo hosts documentation and demonstration notebooks for all the data that is managed by AI for Earth. It also serves as a "staging ground" for the Planetary Computer Data Catalog.

Benchmark various LLM Structured Output frameworks like Instructor, Mirascope, Langchain, LlamaIndex, Fructose, Marvin, Outlines, LMFormatEnforcer, etc on tasks like multi-label classification, named entity recognition, synthetic data generation. The tool provides benchmark results, methodology, instructions to run the benchmark, add new data, and add a new framework. It also includes a roadmap for framework-related tasks, contribution guidelines, citation information, and feedback request.

FoundationaLLM is a platform designed for deploying, scaling, securing, and governing generative AI in enterprises. It allows users to create AI agents grounded in enterprise data, integrate REST APIs, experiment with large language models, centrally manage AI agents and assets, deploy scalable vectorization data pipelines, enable non-developer users to create their own AI agents, control access with role-based access controls, and harness capabilities from Azure AI and Azure OpenAI. The platform simplifies integration with enterprise data sources, provides fine-grain security controls, load balances across multiple endpoints, and is extensible to new data sources and orchestrators. FoundationaLLM addresses the need for customized copilots or AI agents that are secure, licensed, flexible, and suitable for enterprise-scale production.

MooER (摩耳) is an LLM-based speech recognition and translation model developed by Moore Threads. It allows users to transcribe speech into text (ASR) and translate speech into other languages (AST) in an end-to-end manner. The model was trained using 5K hours of data and is now also available with an 80K hours version. MooER is the first LLM-based speech model trained and inferred using domestic GPUs. The repository includes pretrained models, inference code, and a Gradio demo for a better user experience.

LinkedIn_AIHawk is an automated tool designed to revolutionize the job search and application process on LinkedIn. It leverages automation and artificial intelligence to efficiently apply to relevant positions, personalize responses, manage application volume, filter listings, generate dynamic resumes, and handle sensitive information securely. The tool aims to save time, increase application relevance, and enhance job search effectiveness in today's competitive landscape.

The Data Scientist Roadmap2024 provides a comprehensive guide to mastering essential tools for data science success. It includes programming languages, machine learning libraries, cloud platforms, and concepts categorized by difficulty. The roadmap covers a wide range of topics from programming languages to machine learning techniques, data visualization tools, and DevOps/MLOps tools. It also includes web development frameworks and specific concepts like supervised and unsupervised learning, NLP, deep learning, reinforcement learning, and statistics. Additionally, it delves into DevOps tools like Airflow and MLFlow, data visualization tools like Tableau and Matplotlib, and other topics such as ETL processes, optimization algorithms, and financial modeling.

DL3DV-10K is a large-scale dataset of real-world scene-level videos with annotations, covering diverse scenes with different levels of reflection, transparency, and lighting. It includes 10,510 multi-view scenes with 51.2 million frames at 4k resolution, and offers benchmark videos for novel view synthesis (NVS) methods. The dataset is designed to facilitate research in deep learning-based 3D vision and provides valuable insights for future research in NVS and 3D representation learning.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

Chat with your data using OpenAI and AI Search. This solution accelerator uses an Azure OpenAI GPT model and an Azure AI Search index generated from your data, which is integrated into a web application to provide a natural language interface, including speech-to-text functionality, for search queries. Users can drag and drop files, point to storage, and take care of technical setup to transform documents. There is a web app that users can create in their own subscription with security and authentication.

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