OAD is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With OAD, users can easily import data from various sources, clean and preprocess data, perform statistical analysis, and create customizable visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, OAD can help you streamline your data analysis workflow and uncover valuable insights from your data.

Scira is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for data exploration, cleaning, and modeling. With Scira, users can easily import datasets, perform statistical analysis, create insightful visualizations, and generate reports. The tool supports various data formats and offers a wide range of statistical functions and visualization options. Whether you are a data scientist, researcher, or student, Scira can help you uncover valuable insights from your data and communicate your findings effectively.

AI_Spectrum is a versatile machine learning library that provides a wide range of tools and algorithms for building and deploying AI models. It offers a user-friendly interface for data preprocessing, model training, and evaluation. With AI_Spectrum, users can easily experiment with different machine learning techniques and optimize their models for various tasks. The library is designed to be flexible and scalable, making it suitable for both beginners and experienced data scientists.

PythonDataScienceFullThrottle is a comprehensive repository containing various Python scripts, libraries, and tools for data science enthusiasts. It includes a wide range of functionalities such as data preprocessing, visualization, machine learning algorithms, and statistical analysis. The repository aims to provide a one-stop solution for individuals looking to dive deep into the world of data science using Python.

Trubrics-sdk is a software development kit designed to facilitate the integration of analytics features into applications. It provides a set of tools and functionalities that enable developers to easily incorporate analytics capabilities, such as data collection, analysis, and reporting, into their software products. The SDK streamlines the process of implementing analytics solutions, allowing developers to focus on building and enhancing their applications' functionality and user experience. By leveraging trubrics-sdk, developers can quickly and efficiently integrate robust analytics features, gaining valuable insights into user behavior and application performance.

Lector is a text analysis tool that helps users extract insights from unstructured text data. It provides functionalities such as sentiment analysis, keyword extraction, entity recognition, and text summarization. With Lector, users can easily analyze large volumes of text data to uncover patterns, trends, and valuable information. The tool is designed to be user-friendly and efficient, making it suitable for both beginners and experienced users in the field of natural language processing and text mining.

Supavec is an open-source tool that serves as an alternative to Carbon.ai. It allows users to build powerful RAG applications using any data source and at any scale. The tool is designed to provide a simple API endpoint for easy integration and usage. Supavec is built with Next.js, Supabase, Tailwind CSS, Bun, and Upstash, offering a robust and flexible solution for application development. Users can refer to the API documentation for detailed information on how to utilize the tool effectively.

Unity Catalog is an open and interoperable catalog for data and AI, supporting multi-format tables, unstructured data, and AI assets. It offers plugin support for extensibility and interoperates with Delta Sharing protocol. The catalog is fully open with OpenAPI spec and OSS implementation, providing unified governance for data and AI with asset-level access control enforced through REST APIs.

Open AI is a powerful tool for artificial intelligence research and development. It provides a wide range of machine learning models and algorithms, making it easier for developers to create innovative AI applications. With Open AI, users can explore cutting-edge technologies such as natural language processing, computer vision, and reinforcement learning. The platform offers a user-friendly interface and comprehensive documentation to support users in building and deploying AI solutions. Whether you are a beginner or an experienced AI practitioner, Open AI offers the tools and resources you need to accelerate your AI projects and stay ahead in the rapidly evolving field of artificial intelligence.

The multimodal cognitive AI repository focuses on research work related to multimodal cognitive artificial intelligence. It explores the integration of multiple modes of data such as text, images, and audio to enhance AI systems' cognitive capabilities. The repository likely contains code, datasets, and research papers related to multimodal AI applications, including natural language processing, computer vision, and audio processing. Researchers and developers interested in advancing AI systems' understanding of multimodal data can find valuable resources and insights in this repository.

OpenIO SDS is a software solution for object storage, targeting very large-scale unstructured data volumes.

A drill of scientific methods, processes, algorithms, and systems to build stories & models. An in-depth learning resource for humans. This repository is designed for individuals aiming to excel in the field of Data and AI, providing video sessions and text content for learning. It caters to those in leadership positions, professionals, and students, emphasizing the need for dedicated effort to achieve excellence in the tech field. The content covers various topics with a focus on practical application.

PicHome is a powerful open-source cloud storage program that efficiently manages various types of files and excels in image and media file management. Its highlights include robust file sharing features and advanced AI-assisted management tools, providing users with a convenient and intelligent file management experience. The program offers diverse list modes, customizable file information display, enhanced quick file preview, advanced tagging, custom cover and preview images, multiple preview images, and multi-library management. Additionally, PicHome features strong file sharing capabilities, allowing users to share entire libraries, create personalized showcase web pages, and build complete data sharing websites. The AI-assisted management aspect includes AI file renaming, tagging, description writing, batch annotation, and file Q&A services, all aimed at improving file management efficiency. PicHome supports a wide range of file formats and can be applied in various scenarios such as e-commerce, gaming, design, development, enterprises, schools, labs, media, and entertainment institutions.

Riona-AI-Agent is a versatile AI chatbot designed to assist users in various tasks. It utilizes natural language processing and machine learning algorithms to understand user queries and provide accurate responses. The chatbot can be integrated into websites, applications, and messaging platforms to enhance user experience and streamline communication. With its customizable features and easy deployment, Riona-AI-Agent is suitable for businesses, developers, and individuals looking to automate customer support, provide information, and engage with users in a conversational manner.

AppFlowy.IO is an open-source alternative to Notion, providing users with control over their data and customizations. It aims to offer functionality, data security, and cross-platform native experience to individuals, as well as building blocks and collaboration infra services to enterprises and hackers. The tool is built with Flutter and Rust, supporting multiple platforms and emphasizing long-term maintainability. AppFlowy prioritizes data privacy, reliable native experience, and community-driven extensibility, aiming to democratize the creation of complex workplace management tools.

SolarLLMZeroToAll is a comprehensive repository that provides a step-by-step guide and resources for learning and implementing Solar Longitudinal Learning Machines (SolarLLM) from scratch. The repository covers various aspects of SolarLLM, including theory, implementation, and applications, making it suitable for beginners and advanced users interested in solar energy forecasting and machine learning. The materials include detailed explanations, code examples, datasets, and visualization tools to facilitate understanding and practical implementation of SolarLLM models.

The Open Data Editor (ODE) is a no-code application to explore, validate and publish data in a simple way. It is an open source project powered by the Frictionless Framework. The ODE is currently available for download and testing in beta.

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.

OAD is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With OAD, users can easily import data from various sources, clean and preprocess data, perform statistical analysis, and create customizable visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, OAD can help you streamline your data analysis workflow and uncover valuable insights from your data.

Streamline Analyst is a cutting-edge, open-source application powered by Large Language Models (LLMs) designed to revolutionize data analysis. This Data Analysis Agent effortlessly automates tasks such as data cleaning, preprocessing, and complex operations like identifying target objects, partitioning test sets, and selecting the best-fit models based on your data. With Streamline Analyst, results visualization and evaluation become seamless. It aims to expedite the data analysis process, making it accessible to all, regardless of their expertise in data analysis. The tool is built to empower users to process data and achieve high-quality visualizations with unparalleled efficiency, and to execute high-performance modeling with the best strategies. Future enhancements include Natural Language Processing (NLP), neural networks, and object detection utilizing YOLO, broadening its capabilities to meet diverse data analysis needs.

This repository is a part of the 13th iT Help Ironman competition, focusing on exploring explainable artificial intelligence (XAI) in machine learning and deep learning. The content covers the basics of XAI, its applications, cases, challenges, and future directions. It also includes practical machine learning algorithms, model deployment, and integration concepts. The author aims to provide detailed resources on AI and share knowledge with the audience through this competition.

The 'crazyai-ml' repository is a collection of resources related to machine learning, specifically focusing on explaining artificial intelligence models. It includes articles, code snippets, and tutorials covering various machine learning algorithms, data analysis, model training, and deployment. The content aims to provide a comprehensive guide for beginners in the field of AI, offering practical implementations and insights into popular machine learning packages and model tuning techniques. The repository also addresses the integration of AI models and frontend-backend concepts, making it a valuable resource for individuals interested in AI applications.

ProX is a lm-based data refinement framework that automates the process of cleaning and improving data used in pre-training large language models. It offers better performance, domain flexibility, efficiency, and cost-effectiveness compared to traditional methods. The framework has been shown to improve model performance by over 2% and boost accuracy by up to 20% in tasks like math. ProX is designed to refine data at scale without the need for manual adjustments, making it a valuable tool for data preprocessing in natural language processing tasks.

LLM4DB is a repository focused on the intersection of Large Language Models (LLMs) and Database technologies. It covers various aspects such as data processing, data analysis, database optimization, and data management for LLMs. The repository includes research papers, tools, and techniques related to leveraging LLMs for tasks like data cleaning, entity matching, schema matching, data discovery, NL2SQL, data exploration, data visualization, knob tuning, query optimization, and database diagnosis.

Chaindesk is a no-code platform that allows users to easily set up a semantic search system for personal data without technical knowledge. It supports loading data from various sources such as raw text, web pages, files (Word, Excel, PowerPoint, PDF, Markdown, Plain Text), and upcoming support for web sites, Notion, and Airtable. The platform offers a user-friendly interface for managing datastores, querying data via a secure API endpoint, and auto-generating ChatGPT Plugins for each datastore. Chaindesk utilizes a Vector Database (Qdrant), Openai's text-embedding-ada-002 for embeddings, and has a chunk size of 1024 tokens. The technology stack includes Next.js, Joy UI, LangchainJS, PostgreSQL, Prisma, and Qdrant, inspired by the ChatGPT Retrieval Plugin.

OAD is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With OAD, users can easily import data from various sources, clean and preprocess data, perform statistical analysis, and create customizable visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, OAD can help you streamline your data analysis workflow and uncover valuable insights from your data.

Defog's SQLCoder is a family of state-of-the-art large language models (LLMs) designed for converting natural language questions into SQL queries. It outperforms popular open-source models like gpt-4 and gpt-4-turbo on SQL generation tasks. SQLCoder has been trained on more than 20,000 human-curated questions based on 10 different schemas, and the model weights are licensed under CC BY-SA 4.0. Users can interact with SQLCoder through the 'transformers' library and run queries using the 'sqlcoder launch' command in the terminal. The tool has been tested on NVIDIA GPUs with more than 16GB VRAM and Apple Silicon devices with some limitations. SQLCoder offers a demo on their website and supports quantized versions of the model for consumer GPUs with sufficient memory.

TableLLM is a large language model designed for efficient tabular data manipulation tasks in real office scenarios. It can generate code solutions or direct text answers for tasks like insert, delete, update, query, merge, and chart operations on tables embedded in spreadsheets or documents. The model has been fine-tuned based on CodeLlama-7B and 13B, offering two scales: TableLLM-7B and TableLLM-13B. Evaluation results show its performance on benchmarks like WikiSQL, Spider, and self-created table operation benchmark. Users can use TableLLM for code and text generation tasks on tabular data.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

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.

VMind is an open-source solution for intelligent visualization, providing an intelligent chart component based on LLM by VisActor. It allows users to create chart narrative works with natural language interaction, edit charts through dialogue, and export narratives as videos or GIFs. The tool is easy to use, scalable, supports various chart types, and offers one-click export functionality. Users can customize chart styles, specify themes, and aggregate data using LLM models. VMind aims to enhance efficiency in creating data visualization works through dialogue-based editing and natural language interaction.

Quadratic is a modern multiplayer spreadsheet application that integrates Python, AI, and SQL functionalities. It aims to streamline team collaboration and data analysis by enabling users to pull data from various sources and utilize popular data science tools. The application supports building dashboards, creating internal tools, mixing data from different sources, exploring data for insights, visualizing Python workflows, and facilitating collaboration between technical and non-technical team members. Quadratic is built with Rust + WASM + WebGL to ensure seamless performance in the browser, and it offers features like WebGL Grid, local file management, Python and Pandas support, Excel formula support, multiplayer capabilities, charts and graphs, and team support. The tool is currently in Beta with ongoing development for additional features like JS support, SQL database support, and AI auto-complete.