DashAI is a powerful tool for building interactive web applications with Python. It allows users to create data visualization dashboards and deploy machine learning models with ease. The tool provides a simple and intuitive way to design and customize web apps without the need for extensive front-end development knowledge. With DashAI, users can easily showcase their data analysis results and predictive models in a user-friendly and interactive manner, making it ideal for data scientists, developers, and business professionals looking to share insights and predictions with stakeholders.

Doris is a lightweight and user-friendly data visualization tool designed for quick and easy exploration of datasets. It provides a simple interface for users to upload their data and generate interactive visualizations without the need for coding. With Doris, users can easily create charts, graphs, and dashboards to analyze and present their data in a visually appealing way. The tool supports various data formats and offers customization options to tailor visualizations to specific needs. Whether you are a data analyst, researcher, or student, Doris simplifies the process of data exploration and presentation.

Onlook is a web scraping tool that allows users to extract data from websites easily and efficiently. It provides a user-friendly interface for creating web scraping scripts and supports various data formats for exporting the extracted data. With Onlook, users can automate the process of collecting information from multiple websites, saving time and effort. The tool is designed to be flexible and customizable, making it suitable for a wide range of web scraping tasks.

Vizra-ADK is a data visualization tool that allows users to create interactive and customizable visualizations for their data. With a user-friendly interface and a wide range of customization options, Vizra-ADK makes it easy for users to explore and analyze their data in a visually appealing way. Whether you're a data scientist looking to create informative charts and graphs, or a business analyst wanting to present your findings in a compelling way, Vizra-ADK has you covered. The tool supports various data formats and provides features like filtering, sorting, and grouping to help users make sense of their data quickly and efficiently.

Waidrin is a powerful web scraping tool that allows users to easily extract data from websites. It provides a user-friendly interface for creating custom web scraping scripts and supports various data formats for exporting the extracted data. With Waidrin, users can automate the process of collecting information from multiple websites, saving time and effort. The tool is designed to be flexible and scalable, making it suitable for both beginners and advanced users in the field of web scraping.

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.

Agent Lightning is a lightweight and efficient tool for automating repetitive tasks in the field of data analysis and machine learning. It provides a user-friendly interface to create and manage automated workflows, allowing users to easily schedule and execute data processing, model training, and evaluation tasks. With its intuitive design and powerful features, Agent Lightning streamlines the process of building and deploying machine learning models, making it ideal for data scientists, machine learning engineers, and AI enthusiasts looking to boost their productivity and efficiency in their projects.

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.

Catwalk is a lightweight and user-friendly tool for visualizing and analyzing data. It provides a simple interface for users to explore and understand their datasets through interactive charts and graphs. With Catwalk, users can easily upload their data, customize visualizations, and gain insights from their data without the need for complex coding or technical skills.

Eridanus is a powerful data visualization tool designed to help users create interactive and insightful visualizations from their datasets. With a user-friendly interface and a wide range of customization options, Eridanus makes it easy for users to explore and analyze their data in a meaningful way. Whether you are a data scientist, business analyst, or student, Eridanus provides the tools you need to communicate your findings effectively and make data-driven decisions.

Arconia is a powerful open-source tool for managing and visualizing data in a user-friendly way. It provides a seamless experience for data analysts and scientists to explore, clean, and analyze datasets efficiently. With its intuitive interface and robust features, Arconia simplifies the process of data manipulation and visualization, making it an essential tool for anyone working with data.

ROGRAG is a powerful open-source tool designed for data analysis and visualization. It provides a user-friendly interface for exploring and manipulating datasets, making it ideal for researchers, data scientists, and analysts. With ROGRAG, users can easily import, clean, analyze, and visualize data to gain valuable insights and make informed decisions. The tool supports a wide range of data formats and offers a variety of statistical and visualization tools to help users uncover patterns, trends, and relationships in their data. Whether you are working on exploratory data analysis, statistical modeling, or data visualization, ROGRAG is a versatile tool that can streamline your workflow and enhance your data analysis capabilities.

Datatune is a data analysis tool designed to help users explore and analyze datasets efficiently. It provides a user-friendly interface for importing, cleaning, visualizing, and modeling data. With Datatune, users can easily perform tasks such as data preprocessing, feature engineering, model selection, and evaluation. The tool offers a variety of statistical and machine learning algorithms to support data analysis tasks. Whether you are a data scientist, analyst, or researcher, Datatune can streamline your data analysis workflow and help you derive valuable insights from your data.

LightLLM is a lightweight library for linear and logistic regression models. It provides a simple and efficient way to train and deploy machine learning models for regression tasks. The library is designed to be easy to use and integrate into existing projects, making it suitable for both beginners and experienced data scientists. With LightLLM, users can quickly build and evaluate regression models using a variety of algorithms and hyperparameters. The library also supports feature engineering and model interpretation, allowing users to gain insights from their data and make informed decisions based on the model predictions.

Superlinked is a compute framework for information retrieval and feature engineering systems, focusing on converting complex data into vector embeddings for RAG, Search, RecSys, and Analytics stack integration. It enables custom model performance in machine learning with pre-trained model convenience. The tool allows users to build multimodal vectors, define weights at query time, and avoid postprocessing & rerank requirements. Users can explore the computational model through simple scripts and python notebooks, with a future release planned for production usage with built-in data infra and vector database integrations.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

DashAI is a powerful tool for building interactive web applications with Python. It allows users to create data visualization dashboards and deploy machine learning models with ease. The tool provides a simple and intuitive way to design and customize web apps without the need for extensive front-end development knowledge. With DashAI, users can easily showcase their data analysis results and predictive models in a user-friendly and interactive manner, making it ideal for data scientists, developers, and business professionals looking to share insights and predictions with stakeholders.

This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources

Ray is a unified framework for scaling AI and Python applications. It consists of a core distributed runtime and a set of AI libraries for simplifying ML compute, including Data, Train, Tune, RLlib, and Serve. Ray runs on any machine, cluster, cloud provider, and Kubernetes, and features a growing ecosystem of community integrations. With Ray, you can seamlessly scale the same code from a laptop to a cluster, making it easy to meet the compute-intensive demands of modern ML workloads.

Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.

Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. It is designed to be easy to get started with and simple to use for Java developers. DJL provides a native Java development experience and allows users to integrate machine learning and deep learning models with their Java applications. The framework is deep learning engine agnostic, enabling users to switch engines at any point for optimal performance. DJL's ergonomic API interface guides users with best practices to accomplish deep learning tasks, such as running inference and training neural networks.

MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). MLflow's current components are: * `MLflow Tracking `_: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI. * `MLflow Projects `_: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others. * `MLflow Models `_: A model packaging format and tools that let you easily deploy the same model (from any ML library) to batch and real-time scoring on platforms such as Docker, Apache Spark, Azure ML and AWS SageMaker. * `MLflow Model Registry `_: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models.

TT-NN is a python & C++ Neural Network OP library. It provides a low-level programming model, TT-Metalium, enabling kernel development for Tenstorrent hardware.

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed. Instead of only relying on code-defined XPath interactions, Skyvern adds computer vision and LLMs to the mix to parse items in the viewport in real-time, create a plan for interaction and interact with them. This approach gives us a few advantages: 1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code 2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate 3. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include: 1. If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16 2. If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!) Want to see examples of Skyvern in action? Jump to #real-world-examples-of- skyvern

PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.

Vanna is an open-source Python framework for SQL generation and related functionality. It uses Retrieval-Augmented Generation (RAG) to train a model on your data, which can then be used to ask questions and get back SQL queries. Vanna is designed to be portable across different LLMs and vector databases, and it supports any SQL database. It is also secure and private, as your database contents are never sent to the LLM or the vector database.

Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

Avalonia-Assistant is an open-source desktop intelligent assistant that aims to provide a user-friendly interactive experience based on the Avalonia UI framework and the integration of Semantic Kernel with OpenAI or other large LLM models. By utilizing Avalonia-Assistant, you can perform various desktop operations through text or voice commands, enhancing your productivity and daily office experience.

Marvin is a lightweight AI toolkit for building natural language interfaces that are reliable, scalable, and easy to trust. Each of Marvin's tools is simple and self-documenting, using AI to solve common but complex challenges like entity extraction, classification, and generating synthetic data. Each tool is independent and incrementally adoptable, so you can use them on their own or in combination with any other library. Marvin is also multi-modal, supporting both image and audio generation as well using images as inputs for extraction and classification. Marvin is for developers who care more about _using_ AI than _building_ AI, and we are focused on creating an exceptional developer experience. Marvin users should feel empowered to bring tightly-scoped "AI magic" into any traditional software project with just a few extra lines of code. Marvin aims to merge the best practices for building dependable, observable software with the best practices for building with generative AI into a single, easy-to-use library. It's a serious tool, but we hope you have fun with it. Marvin is open-source, free to use, and made with 💙 by the team at Prefect.

Activepieces is an open source replacement for Zapier, designed to be extensible through a type-safe pieces framework written in Typescript. It features a user-friendly Workflow Builder with support for Branches, Loops, and Drag and Drop. Activepieces integrates with Google Sheets, OpenAI, Discord, and RSS, along with 80+ other integrations. The list of supported integrations continues to grow rapidly, thanks to valuable contributions from the community. Activepieces is an open ecosystem; all piece source code is available in the repository, and they are versioned and published directly to npmjs.com upon contributions. If you cannot find a specific piece on the pieces roadmap, please submit a request by visiting the following link: Request Piece Alternatively, if you are a developer, you can quickly build your own piece using our TypeScript framework. For guidance, please refer to the following guide: Contributor's Guide