AI tools for deploy machine learning APIs
Related Tools:
Obviously AI
Obviously AI is a no-code AI tool that allows users to build and deploy machine learning models without writing any code. It is designed to be easy to use, even for those with no data science experience. Obviously AI offers a variety of features, including model building, model deployment, model monitoring, and integration with other tools. It also provides expert support from a dedicated data scientist.
Mystic.ai
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.
Intuition Machines
Intuition Machines is a leading provider of Privacy-Preserving AI/ML platforms and research solutions. They offer products and services that cater to category leaders worldwide, focusing on AI/ML research, security, and risk analysis. Their innovative solutions help enterprises prepare for the future by leveraging AI for a wide range of problems. With a strong emphasis on privacy and security, Intuition Machines is at the forefront of developing cutting-edge AI technologies.
Graphcore
Graphcore is a cloud-based platform that accelerates machine learning processes by harnessing the power of IPU-powered generative AI. It offers cloud services, pre-trained models, optimized inference engines, and APIs to streamline operations and bring intelligence to enterprise applications. With Graphcore, users can build and deploy AI-native products and platforms using the latest AI technologies such as LLMs, NLP, and Computer Vision.
Replicate
Replicate is an AI tool that allows users to run and fine-tune open-source models, deploy custom models at scale, and generate images, text, videos, music, and speech with just one line of code. It provides a platform for the community to contribute and explore thousands of production-ready AI models, enabling users to push the boundaries of AI beyond academic papers and demos. With features like fine-tuning models, deploying custom models, and scaling on Replicate, users can easily create and deploy AI solutions for various tasks.
TensorFlow
TensorFlow is an end-to-end platform for machine learning. It provides a wide range of tools and resources to help developers build, train, and deploy ML models. TensorFlow is used by researchers and developers all over the world to solve real-world problems in a variety of domains, including computer vision, natural language processing, and robotics.
Goptimise
Goptimise is a no-code AI-powered scalable backend builder that helps developers craft scalable, seamless, powerful, and intuitive backend solutions. It offers a solid foundation with robust and scalable infrastructure, including dedicated infrastructure, security, and scalability. Goptimise simplifies software rollouts with one-click deployment, automating the process and amplifying productivity. It also provides smart API suggestions, leveraging AI algorithms to offer intelligent recommendations for API design and accelerating development with automated recommendations tailored to each project. Goptimise's intuitive visual interface and effortless integration make it easy to use, and its customizable workspaces allow for dynamic data management and a personalized development experience.
Shaped
Shaped is a cloud-based platform that provides APIs and tools for building and deploying ranking systems. It offers a variety of features to help developers quickly and easily create and manage ranking models, including a multi-connector SQL interface, a real-time feature store, and a library of pre-built models. Shaped is designed to be scalable, cost-efficient, and easy to use, making it a great option for businesses of all sizes.
Lettria
Lettria is a no-code AI platform for text that helps users turn unstructured text data into structured knowledge. It combines the best of Large Language Models (LLMs) and symbolic AI to overcome current limitations in knowledge extraction. Lettria offers a suite of APIs for text cleaning, text mining, text classification, and prompt engineering. It also provides a Knowledge Studio for building knowledge graphs and private GPT models. Lettria is trusted by large organizations such as AP-HP and Leroy Merlin to improve their data analysis and decision-making processes.
ConsoleX
ConsoleX is an advanced AI tool that offers a wide range of functionalities to unlock infinite possibilities in the field of artificial intelligence. It provides users with a powerful platform to develop, test, and deploy AI models with ease. With cutting-edge features and intuitive interface, ConsoleX is designed to cater to the needs of both beginners and experts in the AI domain. Whether you are a data scientist, researcher, or developer, ConsoleX empowers you to explore the full potential of AI technology and drive innovation in your projects.
Novita AI
Novita AI is an AI cloud platform that offers Model APIs, Serverless, and GPU Instance solutions integrated into one cost-effective platform. It provides tools for building AI products, scaling with serverless architecture, and deploying with GPU instances. Novita AI caters to startups and businesses looking to leverage AI technologies without the need for extensive machine learning expertise. The platform also offers a Startup Program, 24/7 service support, and has received positive feedback for its reasonable pricing and stable API services.
Helix AI
Helix AI is a private GenAI platform that enables users to build AI applications using open source models. The platform offers tools for RAG (Retrieval-Augmented Generation) and fine-tuning, allowing deployment on-premises or in a Virtual Private Cloud (VPC). Users can access curated models, utilize Helix API tools to connect internal and external APIs, embed Helix Assistants into websites/apps for chatbot functionality, write AI application logic in natural language, and benefit from the innovative RAG system for Q&A generation. Additionally, users can fine-tune models for domain-specific needs and deploy securely on Kubernetes or Docker in any cloud environment. Helix Cloud offers free and premium tiers with GPU priority, catering to individuals, students, educators, and companies of varying sizes.
Fifi.ai
Fifi.ai is a managed AI cloud platform that provides users with the infrastructure and tools to deploy and run AI models. The platform is designed to be easy to use, with a focus on plug-and-play functionality. Fifi.ai also offers a range of customization and fine-tuning options, allowing users to tailor the platform to their specific needs. The platform is supported by a team of experts who can provide assistance with onboarding, API integration, and troubleshooting.
BentoML
BentoML is a platform for software engineers to build, ship, and scale AI products. It provides a unified AI application framework that makes it easy to manage and version models, create service APIs, and build and run AI applications anywhere. BentoML is used by over 1000 organizations and has a global community of over 3000 members.
Alltius
Alltius is a platform that allows users to build and deploy AI assistants for sales and support teams. The platform provides a variety of tools and features to help users create assistants that are accurate, secure, and easy to use. Alltius's assistants can be used to automate a variety of tasks, such as answering customer questions, generating leads, and scheduling appointments. The platform also includes a library of pre-built skills that can be used to add functionality to assistants.
Fetch AI
Fetch AI is an open platform that allows users to build, deploy, and monetize AI applications and services. It provides a new AI economy by connecting multiple integrations to create new services and offers a range of features to transform legacy systems to be AI ready without changing existing APIs. The platform enables users to make their services discoverable on the Fetch.ai Platform with the first open network for AI Agents.
Dify
Dify is an open-source platform for building AI applications that combines Backend-as-a-Service and LLMOps to streamline the development of generative AI solutions. It integrates support for mainstream LLMs, an intuitive Prompt orchestration interface, high-quality RAG engines, a flexible AI Agent framework, and easy-to-use interfaces and APIs. Dify allows users to skip complexity and focus on creating innovative AI applications that solve real-world problems. It offers a comprehensive, production-ready solution with a user-friendly interface.
LangChain
LangChain is a framework for developing applications powered by large language models (LLMs). It simplifies every stage of the LLM application lifecycle, including development, productionization, and deployment. LangChain consists of open-source libraries such as langchain-core, langchain-community, and partner packages. It also includes LangGraph for building stateful agents and LangSmith for debugging and monitoring LLM applications.
NetMind
NetMind is an AI tool that offers a Model Library, Enterprise AI Solutions, and AI Consulting services. It provides cutting-edge inference capabilities, model APIs for various data types, and GPU clusters for accelerated performance. The platform allows rapid deployment of models with flexible scaling options. NetMind caters to a wide range of industries, offering solutions that enhance accuracy, cut costs, and accelerate decision-making processes.
Groq
Groq is a fast AI inference tool that offers instant intelligence for openly-available models like Llama 3.1. It provides ultra-low-latency inference for cloud deployments and is compatible with other providers like OpenAI. Groq's speed is proven to be instant through independent benchmarks, and it powers leading openly-available AI models such as Llama, Mixtral, Gemma, and Whisper. The tool has gained recognition in the industry for its high-speed inference compute capabilities and has received significant funding to challenge established players like Nvidia.
Azure Mentor
Expert in Azure's latest services, including Application Insights, API Management, and more.
![[latest] FastAPI GPT Screenshot](/screenshots_gpts/g-BhYCAfVXk.jpg)
[latest] FastAPI GPT
Up-to-date FastAPI coding assistant with knowledge of the latest version. Part of the [latest] GPTs family.
API Alchemist
Advanced tool for creating GPT APIs, specialized in code and OpenAPI Schemas.
Apple CoreML Complete Code Expert
A detailed expert trained on all 3,018 pages of Apple CoreML, offering complete coding solutions. Saving time? https://www.buymeacoffee.com/parkerrex ☕️❤️
Tech Tutor
A tech guide for software engineers, focusing on the latest tools and foundational knowledge.
Streamlit Assistant
This GPT can read all Streamlit Documantation and helps you about Streamlit.
AI Engineering
AI engineering expert offering insights into machine learning and AI development.
Gary Marcus AI Critic Simulator
Humorous AI critic known for skepticism, contradictory arguments, and combining Animal and Machine Learning related Terms.
ecosystem.Ai Use Case Designer v2
The use case designer is configured with the latest Data Science and Behavioral Social Science insights to guide you through the process of defining AI and Machine Learning use cases for the ecosystem.Ai platform.
HuggingFace Helper
A witty yet succinct guide for HuggingFace, offering technical assistance on using the platform - based on their Learning Hub
llmops-duke-aipi
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.
python-aiplatform
The Vertex AI SDK for Python is a library that provides a convenient way to use the Vertex AI API. It offers a high-level interface for creating and managing Vertex AI resources, such as datasets, models, and endpoints. The SDK also provides support for training and deploying custom models, as well as using AutoML models. With the Vertex AI SDK for Python, you can quickly and easily build and deploy machine learning models on Vertex AI.
AITreasureBox
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.
web-llm
WebLLM is a modular and customizable javascript package that directly brings language model chats directly onto web browsers with hardware acceleration. Everything runs inside the browser with no server support and is accelerated with WebGPU. WebLLM is fully compatible with OpenAI API. That is, you can use the same OpenAI API on any open source models locally, with functionalities including json-mode, function-calling, streaming, etc. We can bring a lot of fun opportunities to build AI assistants for everyone and enable privacy while enjoying GPU acceleration.
vertex-ai-mlops
Vertex AI is a platform for end-to-end model development. It consist of core components that make the processes of MLOps possible for design patterns of all types.
llm-app
Pathway's LLM (Large Language Model) Apps provide a platform to quickly deploy AI applications using the latest knowledge from data sources. The Python application examples in this repository are Docker-ready, exposing an HTTP API to the frontend. These apps utilize the Pathway framework for data synchronization, API serving, and low-latency data processing without the need for additional infrastructure dependencies. They connect to document data sources like S3, Google Drive, and Sharepoint, offering features like real-time data syncing, easy alert setup, scalability, monitoring, security, and unification of application logic.
generative-ai-sagemaker-cdk-demo
This repository showcases how to deploy generative AI models from Amazon SageMaker JumpStart using the AWS CDK. Generative AI is a type of AI that can create new content and ideas, such as conversations, stories, images, videos, and music. The repository provides a detailed guide on deploying image and text generative AI models, utilizing pre-trained models from SageMaker JumpStart. The web application is built on Streamlit and hosted on Amazon ECS with Fargate. It interacts with the SageMaker model endpoints through Lambda functions and Amazon API Gateway. The repository also includes instructions on setting up the AWS CDK application, deploying the stacks, using the models, and viewing the deployed resources on the AWS Management Console.
caikit
Caikit is an AI toolkit that enables users to manage models through a set of developer friendly APIs. It provides a consistent format for creating and using AI models against a wide variety of data domains and tasks.
mlflow
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 <https://mlflow.org/docs/latest/tracking.html>`_: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI. * `MLflow Projects <https://mlflow.org/docs/latest/projects.html>`_: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others. * `MLflow Models <https://mlflow.org/docs/latest/models.html>`_: 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 <https://mlflow.org/docs/latest/model-registry.html>`_: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models.
awesome-production-llm
This repository is a curated list of open-source libraries for production large language models. It includes tools for data preprocessing, training/finetuning, evaluation/benchmarking, serving/inference, application/RAG, testing/monitoring, and guardrails/security. The repository also provides a new category called LLM Cookbook/Examples for showcasing examples and guides on using various LLM APIs.
vulcan-sql
VulcanSQL is an Analytical Data API Framework for AI agents and data apps. It aims to help data professionals deliver RESTful APIs from databases, data warehouses or data lakes much easier and secure. It turns your SQL into APIs in no time!
Fueling-Ambitions-Via-Book-Discoveries
Fueling-Ambitions-Via-Book-Discoveries is an Advanced Machine Learning & AI Course designed for students, professionals, and AI researchers. The course integrates rigorous theoretical foundations with practical coding exercises, ensuring learners develop a deep understanding of AI algorithms and their applications in finance, healthcare, robotics, NLP, cybersecurity, and more. Inspired by MIT, Stanford, and Harvard’s AI programs, it combines academic research rigor with industry-standard practices used by AI engineers at companies like Google, OpenAI, Facebook AI, DeepMind, and Tesla. Learners can learn 50+ AI techniques from top Machine Learning & Deep Learning books, code from scratch with real-world datasets, projects, and case studies, and focus on ML Engineering & AI Deployment using Django & Streamlit. The course also offers industry-relevant projects to build a strong AI portfolio.
pytorch-lightning
PyTorch Lightning is a framework for training and deploying AI models. It provides a high-level API that abstracts away the low-level details of PyTorch, making it easier to write and maintain complex models. Lightning also includes a number of features that make it easy to train and deploy models on multiple GPUs or TPUs, and to track and visualize training progress. PyTorch Lightning is used by a wide range of organizations, including Google, Facebook, and Microsoft. It is also used by researchers at top universities around the world. Here are some of the benefits of using PyTorch Lightning: * **Increased productivity:** Lightning's high-level API makes it easy to write and maintain complex models. This can save you time and effort, and allow you to focus on the research or business problem you're trying to solve. * **Improved performance:** Lightning's optimized training loops and data loading pipelines can help you train models faster and with better performance. * **Easier deployment:** Lightning makes it easy to deploy models to a variety of platforms, including the cloud, on-premises servers, and mobile devices. * **Better reproducibility:** Lightning's logging and visualization tools make it easy to track and reproduce training results.
SynapseML
SynapseML (previously known as MMLSpark) is an open-source library that simplifies the creation of massively scalable machine learning (ML) pipelines. It provides simple, composable, and distributed APIs for various machine learning tasks such as text analytics, vision, anomaly detection, and more. Built on Apache Spark, SynapseML allows seamless integration of models into existing workflows. It supports training and evaluation on single-node, multi-node, and resizable clusters, enabling scalability without resource wastage. Compatible with Python, R, Scala, Java, and .NET, SynapseML abstracts over different data sources for easy experimentation. Requires Scala 2.12, Spark 3.4+, and Python 3.8+.
stm32ai-modelzoo
The STM32 AI model zoo is a collection of reference machine learning models optimized to run on STM32 microcontrollers. It provides a large collection of application-oriented models ready for re-training, scripts for easy retraining from user datasets, pre-trained models on reference datasets, and application code examples generated from user AI models. The project offers training scripts for transfer learning or training custom models from scratch. It includes performances on reference STM32 MCU and MPU for float and quantized models. The project is organized by application, providing step-by-step guides for training and deploying models.
llm-app-stack
LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.