Best AI tools for< Manage Ml Features >

Hopsworks is an AI platform that offers a comprehensive solution for building, deploying, and monitoring machine learning systems. It provides features such as a Feature Store, real-time ML capabilities, and generative AI solutions. Hopsworks enables users to develop and deploy reliable AI systems, orchestrate and monitor models, and personalize machine learning models with private data. The platform supports batch and real-time ML tasks, with the flexibility to deploy on-premises or in the cloud.

Keylabs is a state-of-the-art data annotation platform that enhances AI projects with highly precise data annotation and innovative tools. It offers image and video annotation, labeling, and ML-assisted features for industries such as automotive, aerial, agriculture, robotics, manufacturing, waste management, medical, healthcare, retail, fashion, sports, security, livestock, construction, and logistics. Keylabs provides advanced annotation tools, built-in machine learning, efficient operation management, and extra high performance to boost the preparation of visual data for machine learning. The platform ensures transparency in pricing with no hidden fees and offers a free trial for users to experience its capabilities.

JFrog ML is an AI platform designed to streamline AI development from prototype to production. It offers a unified MLOps platform to build, train, deploy, and manage AI workflows at scale. With features like Feature Store, LLMOps, and model monitoring, JFrog ML empowers AI teams to collaborate efficiently and optimize AI & ML models in production.

Union.ai is an infrastructure platform designed for AI, ML, and data workloads. It offers a scalable MLOps platform that optimizes resources, reduces costs, and fosters collaboration among team members. Union.ai provides features such as declarative infrastructure, data lineage tracking, accelerated datasets, and more to streamline AI orchestration on Kubernetes. It aims to simplify the management of AI, ML, and data workflows in production environments by addressing complexities and offering cost-effective strategies.

V7 is an AI data engine for computer vision and generative AI. It provides a multimodal automation tool that helps users label data 10x faster, power AI products via API, build AI + human workflows, and reach 99% AI accuracy. V7's platform includes features such as automated annotation, DICOM annotation, dataset management, model management, image annotation, video annotation, document processing, and labeling services.

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.

Leapmax is a workforce analytics software designed to enhance operational efficiency by improving employee productivity, ensuring data security, facilitating communication and collaboration, and managing compliance. The application offers features such as productivity management, data security, remote team collaboration, reporting management, and network health monitoring. Leapmax provides advantages like AI-based user detection, real-time activity tracking, remote co-browsing, collaboration suite, and actionable analytics. However, some disadvantages include the need for employee monitoring, potential privacy concerns, and dependency on internet connectivity. The application is commonly used by contact centers, outsourcers, enterprises, and back offices. Users can perform tasks like productivity monitoring, app usage tracking, communication and collaboration, compliance management, and remote workforce monitoring.

Functionize is an AI-powered test automation platform that helps enterprises improve their product quality and release faster. It uses machine learning to automate test creation, maintenance, and execution, and provides a range of features to help teams collaborate and manage their testing process. Functionize integrates with popular CI/CD tools and DevOps pipelines, and offers a range of pricing options to suit different needs.

Seldon is an MLOps platform that helps enterprises deploy, monitor, and manage machine learning models at scale. It provides a range of features to help organizations accelerate model deployment, optimize infrastructure resource allocation, and manage models and risk. Seldon is trusted by the world's leading MLOps teams and has been used to install and manage over 10 million ML models. With Seldon, organizations can reduce deployment time from months to minutes, increase efficiency, and reduce infrastructure and cloud costs.

Bloosk AI is an advanced AI tool designed to help businesses with tech transformation, AI and ML product management, data analytics, visualization, predictive analytics, and more. It offers a wide range of features and advantages to streamline operations and enhance decision-making processes. With a focus on AI and ML engineering, architecture, and user experience, Bloosk AI aims to empower organizations to leverage the power of artificial intelligence for improved performance and productivity.

VoteMinecraftServers is a modern Minecraft voting website that provides real-time live analytics to help users stay ahead in the game. It utilizes advanced AI and ML technologies to deliver accurate and up-to-date information. The website is free to use and offers a range of features, including premium commands for enhanced functionality. VoteMinecraftServers is committed to data security and user privacy, ensuring a safe and reliable experience.

Kofluence is a disruptive AI-powered Ad-Tech influencer marketing platform that empowers both brands and influencers to capitalize on the value of their social influence. With features like data-driven performance, matchmaking through AI, end-to-end campaign management, real-time performance metrics, and integration with marketing tools, Kofluence offers a comprehensive solution for effective influencer marketing campaigns. The platform boasts a vast network of over 650,000 creators, deep profiling capabilities, AI/ML algorithms, and proprietary risk and fraud detection mechanisms to ensure successful and optimized campaigns.

Baseten is a machine learning infrastructure that provides a unified platform for data scientists and engineers to build, train, and deploy machine learning models. It offers a range of features to simplify the ML lifecycle, including data preparation, model training, and deployment. Baseten also provides a marketplace of pre-built models and components that can be used to accelerate the development of ML applications.

Automi is an AI-powered platform that helps businesses automate their customer service and support operations. It uses natural language processing (NLP) and machine learning (ML) to understand customer queries and provide relevant answers. Automi also offers a range of features to help businesses manage their customer interactions, including a knowledge base, ticketing system, and live chat.

Cyguru is an all-in-one cloud-based AI Security Operation Center (SOC) that offers a comprehensive range of features for a robust and secure digital landscape. Its Security Operation Center is the cornerstone of its service domain, providing AI-Powered Attack Detection, Continuous Monitoring for Vulnerabilities and Misconfigurations, Compliance Assurance, SecPedia: Your Cybersecurity Knowledge Hub, and Advanced ML & AI Detection. Cyguru's AI-Powered Analyst promptly alerts users to any suspicious behavior or activity that demands attention, ensuring timely delivery of notifications. The platform is accessible to everyone, with up to three free servers and subsequent pricing that is more than 85% below the industry average.

BuildAi is an AI tool designed to provide the lowest cost GPU cloud for AI training on the market. The platform is powered with renewable energy, enabling companies to train AI models at a significantly reduced cost. BuildAi offers interruptible pricing, short term reserved capacity, and high uptime pricing options. The application focuses on optimizing infrastructure for training and fine-tuning machine learning models, not inference, and aims to decrease the impact of computing on the planet. With features like data transfer support, SSH access, and monitoring tools, BuildAi offers a comprehensive solution for ML teams.

The website offers a Synthetic Data Generation platform with the highest accuracy for free. It provides detailed information on synthetic data, data anonymization, and features a Python Client for data generation. The platform ensures privacy and security, allowing users to create fully anonymous synthetic data from original data. It supports various AI/ML use cases, self-service analytics, testing & QA, and data sharing. The platform is designed for Enterprise organizations, offering scalability, privacy by design, and the world's most accurate synthetic data.

Tecton is an AI data platform that helps build smarter AI applications by simplifying feature engineering, generating training data, serving real-time data, and enhancing AI models with context-rich prompts. It automates data pipelines, improves model accuracy, and lowers production costs, enabling faster deployment of AI models. Tecton abstracts away data complexity, provides a developer-friendly experience, and allows users to create features from any source. Trusted by top engineering teams, Tecton streamlines ML delivery processes, improves customer interactions, and automates release processes through CI/CD pipelines.

ClosedLoop is a healthcare data science platform that helps organizations improve outcomes and reduce unnecessary costs with accurate, explainable, and actionable predictions of individual-level health risks. The platform provides a comprehensive library of easily modifiable templates for healthcare-specific predictive models, machine learning (ML) features, queries, and data transformation, which accelerates time to value. ClosedLoop's AI/ML platform is designed exclusively for the data science needs of modern healthcare organizations and helps deliver measurable clinical and financial impact.

Tribe AI is a modern consultancy specializing in AI, data, and machine learning, helping organizations leverage artificial intelligence. The platform offers bespoke AI solutions, advisory services, and GenAI acceleration to unlock the potential of cutting-edge technology. Tribe AI connects top AI talent with companies across various industries, such as healthcare, venture capital, insurance, private equity, and technology, to optimize operations and drive innovation. The platform also features a network of experienced AI researchers, data scientists, ML engineers, and AI fairness experts, ensuring high-quality and secure AI solutions for clients.

Ryoma is an AI Powered Data Agent framework that offers a comprehensive solution for data analysis, engineering, and visualization. It leverages cutting-edge technologies like Langchain, Reflex, Apache Arrow, Jupyter Ai Magics, Amundsen, Ibis, and Feast to provide seamless integration of language models, build interactive web applications, handle in-memory data efficiently, work with AI models, and manage machine learning features in production. Ryoma also supports various data sources like Snowflake, Sqlite, BigQuery, Postgres, MySQL, and different engines like Apache Spark and Apache Flink. The tool enables users to connect to databases, run SQL queries, and interact with data and AI models through a user-friendly UI called Ryoma Lab.

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.

Hopsworks is a data platform for ML with a Python-centric Feature Store and MLOps capabilities. It provides collaboration for ML teams, offering a secure, governed platform for developing, managing, and sharing ML assets. Hopsworks supports project-based multi-tenancy, team collaboration, development tools for Data Science, and is available on any platform including managed cloud services and on-premise installations. The platform enables end-to-end responsibility from raw data to managed features and models, supports versioning, lineage, and provenance, and facilitates the complete MLOps life cycle.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

LanceDB is an open-source database for vector-search built with persistent storage, which greatly simplifies retrieval, filtering, and management of embeddings. The key features of LanceDB include: Production-scale vector search with no servers to manage. Store, query, and filter vectors, metadata, and multi-modal data (text, images, videos, point clouds, and more). Support for vector similarity search, full-text search, and SQL. Native Python and Javascript/Typescript support. Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index(*). Ecosystem integrations with LangChain 🦜️🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB, and more on the way. LanceDB's core is written in Rust 🦀 and is built using Lance, an open-source columnar format designed for performant ML workloads.

Cosdata is a cutting-edge AI data platform designed to power the next generation search pipelines. It features immutability, version control, and excels in semantic search, structured knowledge graphs, hybrid search capabilities, real-time search at scale, and ML pipeline integration. The platform is customizable, scalable, efficient, enterprise-grade, easy to use, and can manage multi-modal data. It offers high performance, indexing, low latency, and high requests per second. Cosdata is designed to meet the demands of modern search applications, empowering businesses to harness the full potential of their data.

HAMi is a Heterogeneous AI Computing Virtualization Middleware designed to manage Heterogeneous AI Computing Devices in a Kubernetes cluster. It allows for device sharing, device memory control, device type specification, and device UUID specification. The tool is easy to use and does not require modifying task YAML files. It includes features like hard limits on device memory, partial device allocation, streaming multiprocessor limits, and core usage specification. HAMi consists of components like a mutating webhook, scheduler extender, device plugins, and in-container virtualization techniques. It is suitable for scenarios requiring device sharing, specific device memory allocation, GPU balancing, low utilization optimization, and scenarios needing multiple small GPUs. The tool requires prerequisites like NVIDIA drivers, CUDA version, nvidia-docker, Kubernetes version, glibc version, and helm. Users can install, upgrade, and uninstall HAMi, submit tasks, and monitor cluster information. The tool's roadmap includes supporting additional AI computing devices, video codec processing, and Multi-Instance GPUs (MIG).

The Python Redis Vector Library (RedisVL) is a tailor-made client for AI applications leveraging Redis. It enhances applications with Redis' speed, flexibility, and reliability, incorporating capabilities like vector-based semantic search, full-text search, and geo-spatial search. The library bridges the gap between the emerging AI-native developer ecosystem and the capabilities of Redis by providing a lightweight, elegant, and intuitive interface. It abstracts the features of Redis into a grammar that is more aligned to the needs of today's AI/ML Engineers or Data Scientists.

Neptune is a scalable experiment tracker for teams training foundation models. Log millions of runs, effortlessly monitor and visualize model training, and deploy on your infrastructure. Track 100% of metadata to accelerate AI breakthroughs. Log and display any framework and metadata type from any ML pipeline. Organize experiments with nested structures and custom dashboards. Compare results, visualize training, and optimize models quicker. Version models, review stages, and access production-ready models. Share results, manage users, and projects. Integrate with 25+ frameworks. Trusted by great companies to improve workflow.

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.

Geoweaver is an in-browser software that enables users to easily compose and execute full-stack data processing workflows using online spatial data facilities, high-performance computation platforms, and open-source deep learning libraries. It provides server management, code repository, workflow orchestration software, and history recording capabilities. Users can run it from both local and remote machines. Geoweaver aims to make data processing workflows manageable for non-coder scientists and preserve model run history. It offers features like progress storage, organization, SSH connection to external servers, and a web UI with Python support.

KitOps is a packaging and versioning system for AI/ML projects that uses open standards so it works with the AI/ML, development, and DevOps tools you are already using. KitOps simplifies the handoffs between data scientists, application developers, and SREs working with LLMs and other AI/ML models. KitOps' ModelKits are a standards-based package for models, their dependencies, configurations, and codebases. ModelKits are portable, reproducible, and work with the tools you already use.

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.

Edgen is a local GenAI API server that serves as a drop-in replacement for OpenAI's API. It provides multi-endpoint support for chat completions and speech-to-text, is model agnostic, offers optimized inference, and features model caching. Built in Rust, Edgen is natively compiled for Windows, MacOS, and Linux, eliminating the need for Docker. It allows users to utilize GenAI locally on their devices for free and with data privacy. With features like session caching, GPU support, and support for various endpoints, Edgen offers a scalable, reliable, and cost-effective solution for running GenAI applications locally.

AnnA is a Python script designed to create filtered decks in optimal review order for Anki flashcards. It uses Machine Learning / AI to ensure semantically linked cards are reviewed far apart. The script helps users manage their daily reviews by creating special filtered decks that prioritize reviewing cards that are most different from the rest. It also allows users to reduce the number of daily reviews while increasing retention and automatically identifies semantic neighbors for each note.

Kollektiv is a Retrieval-Augmented Generation (RAG) system designed to enable users to chat with their favorite documentation easily. It aims to provide LLMs with access to the most up-to-date knowledge, reducing inaccuracies and improving productivity. The system utilizes intelligent web crawling, advanced document processing, vector search, multi-query expansion, smart re-ranking, AI-powered responses, and dynamic system prompts. The technical stack includes Python/FastAPI for backend, Supabase, ChromaDB, and Redis for storage, OpenAI and Anthropic Claude 3.5 Sonnet for AI/ML, and Chainlit for UI. Kollektiv is licensed under a modified version of the Apache License 2.0, allowing free use for non-commercial purposes.

Agentarium is a powerful Python framework for managing and orchestrating AI agents with ease. It provides a flexible and intuitive way to create, manage, and coordinate interactions between multiple AI agents in various environments. The framework offers advanced agent management, robust interaction management, a checkpoint system for saving and restoring agent states, data generation through agent interactions, performance optimization, flexible environment configuration, and an extensible architecture for customization.

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Godot RL Agents is an open-source package that facilitates the integration of Machine Learning algorithms with games created in the Godot Engine. It provides interfaces for popular RL frameworks, support for memory-based agents, 2D and 3D games, AI sensors, and is licensed under MIT. Users can train agents in the Godot editor, create custom environments, export trained agents in ONNX format, and utilize advanced features like different RL training frameworks.

Formador para la certificación de ML Engineer en GCP, con respuestas y explicaciones detalladas.

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I'm a Python and PyTorch expert with knowledge of ML infrastructure requirements ready to help you build and scale your ML projects.

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A simulation game where players learn grow medicinal plants, craft remedies, and manage a herbal healing garden. Another AI Tiny Game by Dave Lalande

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