Best AI tools for< Analyze Dataset Performance >

Zelma is an AI-powered research assistant that enables users to find, graph, and understand U.S. school testing data using plain English queries. It allows users to search student test data by school district, demographics, grade, and more, and presents the results with graphs, tables, and descriptions. Zelma aims to make education data accessible and understandable for everyone.

Zipscore.ai is an AI-powered platform that offers advanced data analytics solutions for businesses. It leverages machine learning algorithms to analyze large datasets and extract valuable insights to drive informed decision-making. The platform is designed to help companies optimize their operations, improve customer engagement, and enhance overall performance through data-driven strategies. With Zipscore.ai, users can easily visualize complex data, identify trends, and predict future outcomes, empowering them to stay ahead in today's competitive market.

CEBRA is a machine-learning method that compresses time series data to reveal hidden structures in the variability of the data. It excels in analyzing behavioral and neural data simultaneously, allowing for the decoding of activity from the visual cortex of the mouse brain to reconstruct viewed videos. CEBRA is a novel encoding method that leverages both behavioral and neural data to produce consistent and high-performance latent spaces, enabling the mapping of space, uncovering complex kinematic features, and providing rapid, high-accuracy decoding of natural movies from the visual cortex.

Mool Capital is an AI-powered platform that offers elevated investing and high fidelity research capabilities. The platform provides revolutionary AI tools for analyzing vast datasets in seconds, trustworthy analysis for informed investing, and performant portfolios curated for optimal performance. Users can access the latest market analysis, investment ideas, and premium articles to enhance their investment decisions. Mool Capital aims to empower investors with AI superpowers to make better investment choices and navigate the complex world of finance with confidence.

Galileo AI is an advanced artificial intelligence tool designed to provide insightful analytics and predictions based on data analysis. The tool utilizes cutting-edge machine learning algorithms to process large datasets and generate valuable insights for businesses and individuals. With Galileo AI, users can make informed decisions, identify trends, and optimize strategies to achieve their goals effectively.

Quadratic is an infinite spreadsheet with Python, SQL, and AI. It combines the familiarity of a spreadsheet with the power of code, allowing users to analyze data, write code, and create visualizations in a single environment. With built-in Python library support, users can bring open source tools directly to their spreadsheets. Quadratic also features real-time collaboration, allowing multiple users to work on the same spreadsheet simultaneously. Additionally, Quadratic is built for speed and performance, utilizing Web Assembly and WebGL to deliver a smooth and responsive experience.

Crustdata is a platform that provides real-time LinkedIn headcount and people data for making informed investment and sales decisions. It offers curated, dynamic data refreshed weekly to help users stay updated on company performance, sales dynamics, investment intelligence, and competitive intelligence. The platform enables users to track companies of interest, enrich CRM systems, and access various datasets related to web traffic, Google search impressions, product reviews, CEO and company reviews, investment data, SEO rankings, company news, and Form D filings. Additionally, Crustdata offers services to identify and fix data gaps, modernize data pipelines, and leverage AI for market mapping and competitor identification.

DataHawk is an eCommerce analytics platform powered by AI that helps users optimize their eCommerce operations from A to Z. It provides competitive intelligence, performance analysis, conversion optimization, sales growth, brand image protection, traffic generation, and more. DataHawk offers automated data collection, composable analytics, AI-powered productivity, integrations, exclusive datasets, and professional services. The platform empowers users with end-to-end visibility, comprehensive marketplace data, flexibility, control over operational data, and expert support. With AI capabilities, DataHawk automates data collection, detects anomalies, generates recommended actions, and augments productivity. The platform enhances revenue, RoAS, and time savings for users, supported by dedicated experts and customer success stories.

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.

Powerdrill is a platform that provides swift insights from knowledge and data. It offers a range of features such as discovering datasets, creating BI dashboards, accessing various apps, resources, blogs, documentation, and changelogs. The platform is available in English and fosters a community through its affiliate program. Users can sign up for a basic plan to start utilizing the tools and services offered by Powerdrill.

LINQ Me Up is an AI-powered tool designed to boost .Net productivity by generating and converting LINQ queries efficiently. It offers fast and reliable conversion of SQL queries to LINQ code, transformation of LINQ code into SQL queries, and tailored LINQ queries for various datasets. The tool supports C# and Visual Basic code, Method and Query syntax, and utilizes AI-powered analysis for optimized results. LINQ Me Up is more versatile and powerful than rule-based or syntax conversions, enabling users to effortlessly migrate, build, and focus on essential code parts.

ChartFast is an AI Data Analyzer tool that automates data visualization and analysis tasks, powered by GPT-4 technology. It allows users to generate precise and sleek graphs in seconds, process vast amounts of data, and provide interactive data queries and quick exports. With features like specialized internal libraries for complex graph generation, customizable visualization code, and instant data export, ChartFast aims to streamline data work and enhance data analysis efficiency.

This AI-powered age detection tool analyzes your photo to estimate how old you look. It utilizes advanced artificial intelligence technology to assess facial characteristics such as wrinkles, skin texture, and facial features, comparing them against a vast dataset to provide an approximation of your age. The tool is free to use and ensures privacy by automatically deleting uploaded photos after analysis.

TextMine is an AI-powered knowledge base designed for businesses to manage and analyze critical documents efficiently. It offers features such as document analysis, smart-search capabilities, automated data extraction, and structured dataset transformation. TextMine helps businesses save time and money by streamlining document management processes and enabling informed decision-making. The application caters to various industries like Technology, Legal Services, and Financial Services, providing solutions for teams in Procurement, Finance, Compliance, CIOs, and CDOs.

Meltwater is an AI-powered media intelligence platform that helps businesses gain competitive insights by analyzing media, social, and consumer trends. With a robust dataset and powerful AI capabilities, Meltwater empowers teams to uncover actionable insights for PR, marketing, and sales strategies. The platform offers tools for media monitoring, social listening, influencer marketing, and more, enabling users to make data-driven decisions and measure the impact of their efforts.

SecureWoof is an AI-powered malware scanner that utilizes advanced technologies such as Yara rules, Retdec unpacker, Ghidra decompiler, clang-tidy formatter, FastText embedding, and RoBERTa transformer network to scan and detect malicious content in executable files. The tool is trained on the SOREL-20M malware dataset to enhance its accuracy and efficiency in identifying threats. SecureWoof offers a public API for easy integration with other applications, making it a versatile solution for cybersecurity professionals and individuals concerned about malware threats.

The website offers an AI-powered binary vulnerability scanner that allows users to upload a binary file for analysis. The tool decompiles the executable, removes filler, formats the code, and checks for vulnerabilities by comparing against a database of historical vulnerabilities. It utilizes a finetuned CodeT5+ Embedding model to generate function-wise embeddings and checks for similarities against the DiverseVul Dataset. The tool also uses SemGrep to identify vulnerabilities in the code.

ITVA is an AI automation tool for network infrastructure products that revolutionizes network management by enabling users to configure, query, and document their network using natural language. It offers features such as rapid configuration deployment, network diagnostics acceleration, automated diagram generation, and modernized IP address management. ITVA's unique solution securely connects to networks, combining real-time data with a proprietary dataset curated by veteran engineers. The tool ensures unparalleled accuracy and insights through its real-time data pipeline and on-demand dynamic analysis capabilities.

LifeArchitect.ai is a leading platform in the field of artificial intelligence (AI), offering a wealth of insights, papers, articles, and videos related to post-2020 AI advancements. Dr. Alan D. Thompson, a renowned expert in AI, focuses on enhancing human intelligence through AI technologies. The platform serves major AI labs, government bodies, research institutes, and individuals interested in the AI revolution, providing comprehensive analyses, reports, and retrospectives on AI progress and future trends.

Genie TechBio is the world's first AI bioinformatician, offering an LLM-powered omics analysis software that operates entirely in natural language, eliminating the need for coding. Researchers can effortlessly analyze extensive datasets by engaging in a conversation with Genie, receiving recommendations for analysis pipelines, and obtaining results. The tool aims to accelerate biomedical research and empower scientists with newfound data analysis capabilities.

This project explores the capability of Large Language Models (LLMs) to perform regression tasks using in-context examples. It compares the performance of LLMs like GPT-4 and Claude 3 Opus with traditional supervised methods such as Linear Regression and Gradient Boosting. The project provides preprints and results demonstrating the strong performance of LLMs in regression tasks. It includes datasets, models used, and experiments on adaptation and contamination. The code and data for the experiments are available for interaction and analysis.

Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. It is a systematic & reusable library of 80+ core OPs, 20+ reusable config recipes, and 20+ feature-rich dedicated toolkits, designed to function independently of specific LLM datasets and processing pipelines. Data-Juicer allows detailed data analyses with an automated report generation feature for a deeper understanding of your dataset. Coupled with multi-dimension automatic evaluation capabilities, it supports a timely feedback loop at multiple stages in the LLM development process. Data-Juicer offers tens of pre-built data processing recipes for pre-training, fine-tuning, en, zh, and more scenarios. It provides a speedy data processing pipeline requiring less memory and CPU usage, optimized for maximum productivity. Data-Juicer is flexible & extensible, accommodating most types of data formats and allowing flexible combinations of OPs. It is designed for simplicity, with comprehensive documentation, easy start guides and demo configs, and intuitive configuration with simple adding/removing OPs from existing configs.

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.

The AV-Deepfake1M repository is the official repository for the paper AV-Deepfake1M: A Large-Scale LLM-Driven Audio-Visual Deepfake Dataset. It addresses the challenge of detecting and localizing deepfake audio-visual content by proposing a dataset containing video manipulations, audio manipulations, and audio-visual manipulations for over 2K subjects resulting in more than 1M videos. The dataset is crucial for developing next-generation deepfake localization methods.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

WordLlama is a fast, lightweight NLP toolkit optimized for CPU hardware. It recycles components from large language models to create efficient word representations. It offers features like Matryoshka Representations, low resource requirements, binarization, and numpy-only inference. The tool is suitable for tasks like semantic matching, fuzzy deduplication, ranking, and clustering, making it a good option for NLP-lite tasks and exploratory analysis.

This repository contains a collection of papers related to tool learning with large language models (LLMs). The papers are organized according to the survey paper 'Tool Learning with Large Language Models: A Survey'. The survey focuses on the benefits and implementation of tool learning with LLMs, covering aspects such as task planning, tool selection, tool calling, response generation, benchmarks, evaluation, challenges, and future directions in the field. It aims to provide a comprehensive understanding of tool learning with LLMs and inspire further exploration in this emerging area.

MMOS (Mix of Minimal Optimal Sets) is a dataset designed for math reasoning tasks, offering higher performance and lower construction costs. It includes various models and data subsets for tasks like arithmetic reasoning and math word problem solving. The dataset is used to identify minimal optimal sets through reasoning paths and statistical analysis, with a focus on QA-pairs generated from open-source datasets. MMOS also provides an auto problem generator for testing model robustness and scripts for training and inference.

Obsei is an open-source, low-code, AI powered automation tool that consists of an Observer to collect unstructured data from various sources, an Analyzer to analyze the collected data with various AI tasks, and an Informer to send analyzed data to various destinations. The tool is suitable for scheduled jobs or serverless applications as all Observers can store their state in databases. Obsei is still in alpha stage, so caution is advised when using it in production. The tool can be used for social listening, alerting/notification, automatic customer issue creation, extraction of deeper insights from feedbacks, market research, dataset creation for various AI tasks, and more based on creativity.

**RVC_CLI: Retrieval-based Voice Conversion Command Line Interface** This command-line interface (CLI) provides a comprehensive set of tools for voice conversion, enabling you to modify the pitch, timbre, and other characteristics of audio recordings. It leverages advanced machine learning models to achieve realistic and high-quality voice conversions. **Key Features:** * **Inference:** Convert the pitch and timbre of audio in real-time or process audio files in batch mode. * **TTS Inference:** Synthesize speech from text using a variety of voices and apply voice conversion techniques. * **Training:** Train custom voice conversion models to meet specific requirements. * **Model Management:** Extract, blend, and analyze models to fine-tune and optimize performance. * **Audio Analysis:** Inspect audio files to gain insights into their characteristics. * **API:** Integrate the CLI's functionality into your own applications or workflows. **Applications:** The RVC_CLI finds applications in various domains, including: * **Music Production:** Create unique vocal effects, harmonies, and backing vocals. * **Voiceovers:** Generate voiceovers with different accents, emotions, and styles. * **Audio Editing:** Enhance or modify audio recordings for podcasts, audiobooks, and other content. * **Research and Development:** Explore and advance the field of voice conversion technology. **For Jobs:** * Audio Engineer * Music Producer * Voiceover Artist * Audio Editor * Machine Learning Engineer **AI Keywords:** * Voice Conversion * Pitch Shifting * Timbre Modification * Machine Learning * Audio Processing **For Tasks:** * Convert Pitch * Change Timbre * Synthesize Speech * Train Model * Analyze Audio

LazyLLM is a low-code development tool for building complex AI applications with multiple agents. It assists developers in building AI applications at a low cost and continuously optimizing their performance. The tool provides a convenient workflow for application development and offers standard processes and tools for various stages of application development. Users can quickly prototype applications with LazyLLM, analyze bad cases with scenario task data, and iteratively optimize key components to enhance the overall application performance. LazyLLM aims to simplify the AI application development process and provide flexibility for both beginners and experts to create high-quality applications.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

PIXIU is a project designed to support the development, fine-tuning, and evaluation of Large Language Models (LLMs) in the financial domain. It includes components like FinBen, a Financial Language Understanding and Prediction Evaluation Benchmark, FIT, a Financial Instruction Dataset, and FinMA, a Financial Large Language Model. The project provides open resources, multi-task and multi-modal financial data, and diverse financial tasks for training and evaluation. It aims to encourage open research and transparency in the financial NLP field.

GuideLLM is a powerful tool for evaluating and optimizing the deployment of large language models (LLMs). By simulating real-world inference workloads, GuideLLM helps users gauge the performance, resource needs, and cost implications of deploying LLMs on various hardware configurations. This approach ensures efficient, scalable, and cost-effective LLM inference serving while maintaining high service quality. Key features include performance evaluation, resource optimization, cost estimation, and scalability testing.

This repository provides a deployment guide for utilizing Google Cloud's Generative AI tools in marketing scenarios. It includes step-by-step instructions, examples of crafting marketing materials, and supplementary Jupyter notebooks. The demos cover marketing insights, audience analysis, trendspotting, content search, content generation, and workspace integration. Users can access and visualize marketing data, analyze trends, improve search experience, and generate compelling content. The repository structure includes backend APIs, frontend code, sample notebooks, templates, and installation scripts.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

AgentNeo is a Python package that provides functionalities for project, trace, dataset, experiment management. It allows users to authenticate, create projects, trace agents and LangGraph graphs, manage datasets, and run experiments with metrics. The tool aims to streamline AI project management and analysis by offering a comprehensive set of features.

Cleanlab helps you **clean** data and **lab** els by automatically detecting issues in a ML dataset. To facilitate **machine learning with messy, real-world data** , this data-centric AI package uses your _existing_ models to estimate dataset problems that can be fixed to train even _better_ models.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

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.

Just upload a numerical dataset for classification task, will apply data analysis and machine learning steps to make a best model possible.

School Advisory with Enhanced Dataset Analysis

Psychology data analysis expert that guides users through structured, step-by-step exploration of a CSV data set. The analysis is based on research questions.

Analyze and interpret datasets on Dutch SaaS companies' employee growth. Created by [E-commercemanagers.com](https://e-commercemanagers.com).

I analyze cognitive biases in scenarios and thoughts, providing neutral, educational insights.

Analyze and reverse engineer images. Receive style descriptions and image re-creation prompts.

I'll help you analyze market news and charts for trading/investing

I read and analyze annual reports of companies. Just upload the annual report PDF and start asking me questions!

As a Good Design Advisor, I provide consultation and advice on design topics and analyze designs that are provided through documents or links. I can also generate visual representations myself to illustrate design concepts.

I analyze historical events, offering insights from multiple perspectives.

For strategic knowledge distillation, upload the document you need to analyze and use !start. ENSURE the uploaded file shows DOCUMENT and NOT PDF. This workflow requires leveraging RAG to operate. Only a small amount of PDFs are supported, convert to txt or doc. For timeout, refresh & !continue

Critically analyze SLIs/SLOs with a deeper, provocative approach

Analyze any uploaded art piece, providing thoughtful insight on the history of the piece and its maker. Replicate art pieces in new styles generated by the user. Be an overall expert in art and help users navigate the art scene. Inform them of different types of art

I analyze situations using game theory to advise on the best strategic approach.

I analyze website screenshots for UI/UX improvements.

A tool for historians to analyze and catalog historical images and documents.

Hone your phishing detection skills! Analyze emails, texts, and calls to spot deception. Become a security pro!

I analyze audition sides to help actors prepare for in-person and self-taped auditions for TV and Film

I analyze food images for FODMAP content using updated guidelines.

A Next.js expert ready to analyze code, answer questions, and offer learning plans.