Best AI tools for< Azure Data Scientist >

The website is Microsoft Azure, a cloud computing service offering a wide range of products and solutions for businesses and developers. Azure provides global infrastructure, FinOps, AI services, compute resources, containers, hybrid and multicloud solutions, analytics, application development, and more. It aims to empower users to innovate, modernize, and scale their applications and workloads efficiently on a secure and flexible cloud platform.

Azure AI Platform by Microsoft offers a comprehensive suite of artificial intelligence services and tools for developers and businesses. It provides a unified platform for building, training, and deploying AI models, as well as integrating AI capabilities into applications. With a focus on generative AI, multimodal models, and large language models, Azure AI empowers users to create innovative AI-driven solutions across various industries. The platform also emphasizes content safety, scalability, and agility in managing AI projects, making it a valuable resource for organizations looking to leverage AI technologies.

integrate.ai is a platform that enables data and analytics providers to collaborate easily with enterprise data science teams without moving data. Powered by federated learning technology, the platform allows for efficient proof of concepts, data experimentation, infrastructure agnostic evaluations, collaborative data evaluations, and data governance controls. It supports various data science jobs such as match rate analysis, exploratory data analysis, correlation analysis, model performance analysis, feature importance & data influence, and model validation. The platform integrates with popular data science tools like Azure, Jupyter, Databricks, AWS, GCP, Snowflake, Pandas, PyTorch, MLflow, and scikit-learn.

Cirrascale Cloud Services is an AI tool that offers cloud solutions for Artificial Intelligence applications. The platform provides a range of cloud services and products tailored for AI innovation, including NVIDIA GPU Cloud, AMD Instinct Series Cloud, Qualcomm Cloud, Graphcore, Cerebras, and SambaNova. Cirrascale's AI Innovation Cloud enables users to test and deploy on leading AI accelerators in one cloud, democratizing AI by delivering high-performance AI compute and scalable deep learning solutions. The platform also offers professional and managed services, tailored multi-GPU server options, and high-throughput storage and networking solutions to accelerate development, training, and inference workloads.

Qubinets is a cloud data environment solutions platform that provides building blocks for building big data, AI, web, and mobile environments. It is an open-source, no lock-in, secured, and private platform that can be used on any cloud, including AWS, Digital Ocean, Google Cloud, and Microsoft Azure. Qubinets makes it easy to plan, build, and run data environments, and it streamlines and saves time and money by reducing the grunt work in setup and provisioning.

Avian is a generative BI platform that uses AI to help businesses uncover insights, create reports, and take transformative action. It is used by professionals at companies such as Google, Salesforce, and Boeing. Avian's AI agents are trained on large language models and can analyze data from a variety of sources, including spreadsheets, Shopify, LinkedIn Ads, BigQuery, Google Analytics 4, Google Ads, Google Search Console, Facebook Ads, and Facebook Insights. Avian is committed to protecting user privacy and operates with secure, SOC/2 approved Open Source Foundation language models on Microsoft Azure.

Vellum AI is an AI platform that supports using Microsoft Azure hosted OpenAI models. It offers tools for prompt engineering, semantic search, prompt chaining, evaluations, and monitoring. Vellum enables users to build AI systems with features like workflow automation, document analysis, fine-tuning, Q&A over documents, intent classification, summarization, vector search, chatbots, blog generation, sentiment analysis, and more. The platform is backed by top VCs and founders of well-known companies, providing a complete solution for building LLM-powered applications.

Mystic.ai is an AI tool designed to deploy and scale Machine Learning models with ease. It offers a fully managed Kubernetes platform that runs in your own cloud, allowing users to deploy ML models in their own Azure/AWS/GCP account or in a shared GPU cluster. Mystic.ai provides cost optimizations, fast inference, simpler developer experience, and performance optimizations to ensure high-performance AI model serving. With features like pay-as-you-go API, cloud integration with AWS/Azure/GCP, and a beautiful dashboard, Mystic.ai simplifies the deployment and management of ML models for data scientists and AI engineers.

LiteLLM is an AI tool that offers a Unified API for Azure OpenAI Vertex AI Bedrock. It provides a proxy server for managing authentication, load balancing, and spend tracking across a wide range of LLMs. LiteLLM is designed to simplify the integration and management of various AI services in the OpenAI format. With features like cloud deployment, open-source availability, and extensive provider integrations, LiteLLM aims to streamline AI development workflows and enhance operational efficiency.

SearchCandy is a Generative AI-powered search and analytics tool designed for e-commerce businesses. It helps businesses understand their customers better, boost conversions, and gain valuable insights. The platform offers easy integration with popular data integrations like Azure, Google Cloud, and AWS, as well as API clients such as Node.js, Python, and .NET. With SearchCandy, businesses can connect their data, test data retrieval using conversational prompts, easily integrate into their e-commerce store, track customer conversions, and benefit from affordable pricing.

Teraflow.ai is an AI-enablement company that specializes in helping businesses adopt and scale their artificial intelligence models. They offer services in data engineering, ML engineering, AI/UX, and cloud architecture. Teraflow.ai assists clients in fixing data issues, boosting ML model performance, and integrating AI into legacy customer journeys. Their team of experts deploys solutions quickly and efficiently, using modern practices and hyper scaler technology. The company focuses on making AI work by providing fixed pricing solutions, building team capabilities, and utilizing agile-scrum structures for innovation. Teraflow.ai also offers certifications in GCP and AWS, and partners with leading tech companies like HashiCorp, AWS, and Microsoft Azure.

Knit is an AI playground for prompt designers. It provides professional prompt editors with various models, including GPT-4-turbo/vision, Claude-3, Gemini-pro, and more. Users can store, edit, and run their prompts in Knit. It also offers project management features, allowing users to organize prompts with projects, set up projects for different use cases, and collaborate with team members. Knit supports different kinds of models, including OpenAI, Claude, Azure OpenAI, and plans to support more in the future. It allows users to control API parameters, export code instantly, and provides security features such as encryption and version control.

AiPlus is an AI tool designed to serve as a cost-efficient model gateway. It offers users a platform to access and utilize various AI models for their projects and tasks. With AiPlus, users can easily integrate AI capabilities into their applications without the need for extensive development or resources. The tool aims to streamline the process of leveraging AI technology, making it accessible to a wider audience.

atQor is an AI consulting company specializing in Azure and Data & AI solutions. They provide services to enterprise clients to lead them in the digital landscape, offering innovative solutions for increased productivity and revenue. With a focus on AI technologies, atQor equips businesses to excel in the AI arena and stay at the forefront of technology.

Microsoft Azure is a cloud computing service that offers a wide range of products and services for businesses and developers. It provides global infrastructure, FinOps capabilities, customer stories, and innovation insights. Azure features include virtual machines, AI services, Kubernetes service, Cosmos DB, and more. The platform supports hybrid and multicloud solutions, analytics, application development, and modernization. Azure also offers resources, pricing tools, and partner programs. With a focus on AI and machine learning, Azure enables responsible AI development and secure cloud solutions. The platform caters to IT professionals, developers, data analysts, business leaders, startups, and students, offering a comprehensive suite of tools and services.

TextUnbox is an AI-powered tool that allows users to extract text from images, generate images from text descriptions, translate text, remove image backgrounds, and more. It supports over 20 languages and can be used in the browser or integrated into custom solutions using its REST API.

BuildShip.com is a powerful AI Assistant Builder that allows users to create AI Assistant ChatBots in just 5 minutes. The platform enables users to connect to tools and databases without the need for any code, offering full flexibility with low-code options. Users can build AI Assistants using popular models like OpenAI, Claude 3, and Azure, and can easily ship their creations as APIs, chat widgets, workflow, or schedule jobs. The platform also provides secure integration with databases, the ability to generate custom action nodes, and seamless plugin chat widgets for websites. BuildShip.com simplifies the process of building AI Assistants and empowers users to bring their ideas to life effortlessly.

CaseMark is an AI-assisted workflow and summarization platform designed for the legal industry. It offers a range of features such as deposition summaries, case summaries, medical records summaries, trial summaries, and custom summaries. The platform leverages AI technology to generate accurate and efficient summaries of complex legal documents in minutes, enabling legal professionals to focus on more critical tasks. CaseMark also provides custom workflows, integration with existing platforms, enterprise-class security, and a money-back guarantee. Trusted by over 4500 lawyers, court reporting firms, and legal tech companies, CaseMark aims to empower legal efficiency one workflow at a time.

Microsoft is a leading technology company that develops, manufactures, licenses, supports, and sells computer software, consumer electronics, personal computers, and services. Its best-known software products are the Microsoft Windows operating system, the Microsoft Office suite, and the Internet Explorer and Edge web browsers. Its hardware products include the Xbox video game consoles and the Surface tablet computers. Microsoft is also a major provider of cloud computing services through its Azure platform.

VoiceGen is an AI audio platform that enables users to create realistic speech using the best technology from leading providers like OpenAI, Google, AWS, and Azure. It offers natural, high-quality voices with support for multiple languages and unrestricted commercial use. VoiceGen prioritizes simplicity, transparency, and innovation, providing an accessible and affordable solution for voice generation needs. The platform ensures security and privacy of user data, offering a pay-as-you-go pricing model with fair and transparent costs.

Azure Functions OpenAI Extension is a project that adds support for OpenAI LLM (GPT-3.5-turbo, GPT-4) bindings in Azure Functions. It provides NuGet packages for various functionalities like text completions, chat completions, assistants, embeddings generators, and semantic search. The project requires .NET 6 SDK or greater, Azure Functions Core Tools v4.x, and specific settings in Azure Function or local settings for development. It offers features like text completions, chat completion, assistants with custom skills, embeddings generators for text relatedness, and semantic search using vector databases. The project also includes examples in C# and Python for different functionalities.

AI-in-a-Box is a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction, while maintaining the highest standards of quality and efficiency. It provides essential guidance on the responsible use of AI and LLM technologies, specific security guidance for Generative AI (GenAI) applications, and best practices for scaling OpenAI applications within Azure. The available accelerators include: Azure ML Operationalization in-a-box, Edge AI in-a-box, Doc Intelligence in-a-box, Image and Video Analysis in-a-box, Cognitive Services Landing Zone in-a-box, Semantic Kernel Bot in-a-box, NLP to SQL in-a-box, Assistants API in-a-box, and Assistants API Bot in-a-box.

LLMOps Duke AIPI is a course focused on operationalizing Large Language Models, teaching methodologies for developing applications using software development best practices with large language models. The course covers various topics such as generative AI concepts, setting up development environments, interacting with large language models, using local large language models, applied solutions with LLMs, extensibility using plugins and functions, retrieval augmented generation, introduction to Python web frameworks for APIs, DevOps principles, deploying machine learning APIs, LLM platforms, and final presentations. Students will learn to build, share, and present portfolios using Github, YouTube, and Linkedin, as well as develop non-linear life-long learning skills. Prerequisites include basic Linux and programming skills, with coursework available in Python or Rust. Additional resources and references are provided for further learning and exploration.

This repository contains samples to help design AI applications using data from an Azure SQL Database. It showcases technical concepts and workflows integrating Azure SQL data with popular AI components both within and outside Azure. The samples cover various AI features such as Azure Cognitive Services, Promptflow, OpenAI, Vanna.AI, Content Moderation, LangChain, and more. Additionally, there are end-to-end samples like Similar Content Finder, Session Conference Assistant, Chatbots, Vectorization, SQL Server Database Development, Redis Vector Search, and Similarity Search with FAISS.

The Enterprise Azure OpenAI Hub is a comprehensive repository designed to guide users through the world of Generative AI on the Azure platform. It offers a structured learning experience to accelerate the transition from concept to production in an Enterprise context. The hub empowers users to explore various use cases with Azure services, ensuring security and compliance. It provides real-world examples and playbooks for practical insights into solving complex problems and developing cutting-edge AI solutions. The repository also serves as a library of proven patterns, aligning with industry standards and promoting best practices for secure and compliant AI development.

Windows Agent Arena (WAA) is a scalable Windows AI agent platform designed for testing and benchmarking multi-modal, desktop AI agents. It provides researchers and developers with a reproducible and realistic Windows OS environment for AI research, enabling testing of agentic AI workflows across various tasks. WAA supports deploying agents at scale using Azure ML cloud infrastructure, allowing parallel running of multiple agents and delivering quick benchmark results for hundreds of tasks in minutes.

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.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

Azure OpenAI demos is a repository showcasing various demos and use cases of Azure OpenAI services. It includes demos for tasks such as image comparisons, car damage copilot, video to checklist generation, automatic data visualization, text analytics, and more. The repository provides a wide range of examples on how to leverage Azure OpenAI for different applications and industries.

This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access the ChatGPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval.

This repository provides resources to understand and utilize GPT (Generative Pre-trained Transformer) by Azure OpenAI. It includes sample solutions, use cases, and quick start guides. Users can explore various applications of GPT, such as chatbots, customer service, and content generation. The repository also offers Langchain, Semantic Kernel, and Prompt Flow samples, along with Serverless SQL GPT for natural language processing in Azure Synapse Analytics. The samples are based on GPT 3.5, with plans to update for GPT-4. Users are encouraged to contribute to keep the repository updated with the latest technologies and solutions.

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.

LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.

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.

This sample shows how to build a serverless chat experience with Retrieval-Augmented Generation using LangChain.js and Azure. The application is hosted on Azure Static Web Apps and Azure Functions, with Azure Cosmos DB for MongoDB vCore as the vector database. You can use it as a starting point for building more complex AI applications.

The .NET Conf Focus on AI 2024 repository contains content from the event focusing on incorporating AI into .NET applications and services. It includes slides and demos showcasing various AI-powered web apps, AI models, generative AI apps, and more. The repository serves as a resource for developers looking to explore AI integration with .NET technologies.

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.

Azure OpenAI Service provides REST API access to OpenAI's powerful language models including GPT-3, Codex and Embeddings. Users can easily adapt models for content generation, summarization, semantic search, and natural language to code translation. The workshop covers basics, prompt engineering, common NLP tasks, generative tasks, conversational dialog, and learning methods. It guides users to build applications with PowerApp, query SQL data, create data pipelines, and work with proprietary datasets. Target audience includes Power Users, Software Engineers, Data Scientists, and AI architects and Managers.

This repository provides code samples in Python, C#, REST, and JavaScript for vector support in Azure AI Search. It includes demos for various languages showcasing vectorization of data, creating indexes, and querying vector data. Additionally, it offers tools like Azure AI Search Lab for experimenting with AI-enabled search scenarios in Azure and templates for deploying custom chat-with-your-data solutions. The repository also features documentation on vector search, hybrid search, creating and querying vector indexes, and REST API references for Azure AI Search and Azure OpenAI Service.

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The KQL Query Helper GPT is tailored specifically for assisting users with Kusto Query Language (KQL) queries. It leverages extensive knowledge from Azure Data Explorer documentation to aid users in understanding, reviewing, and creating new KQL queries based on their prompts.

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