Mlops
45 items across the graph — tagged with Mlops.
From the graph · 45
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdran…
Machine Learning Engineering Open Book
The absolute trainer to light up AI agents.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines…
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
The Open Source Feature Store for AI/ML
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
:sunglasses: A curated list of awesome MLOps tools
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
Curated list of the best truly open-source AI projects, models, tools, and infrastructure. Daily updated.
Machine Learning Pipelines for Kubeflow
⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers…
Community maintained hardware plugin for vLLM on Ascend
Automated Machine Learning on Kubernetes
MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your developme…
🔥 Real-time NVIDIA GPU dashboard
A comprehensive Python package template to kickstart and standardize your MLOps initiatives and data pipelines.
A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
Learn how to create, develop, and maintain a state-of-the-art MLOps code base
NucliaDB, The AI Search database for RAG
Google Cloud Platform Vertex AI end-to-end workflows for machine learning operations
This repo provides a customizable stack for starting new ML projects on Databricks that follow production best-practices out of the box.
BharatMLStack is an open-source, end-to-end machine learning infrastructure stack built at Meesho to support real-time and batch ML workloads at Bharat scale
skops is a Python library helping you share your scikit-learn based models and put them in production
Start building and deploying Python packages and Docker images for MLOps tasks.
A curated list of MLSecOps tools and resources for securing machine learning and AI systems - adversarial ML defense, LLM security, AI red teaming, model scanni…
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
Gokart solves reproducibility, task dependencies, constraints of good code, and ease of use for Machine Learning Pipeline.
Agent traces you can run, not just read.
Examples of models deployable with Truss
Python SDK for healthcare AI — typed, validated FHIR tools for agents, real-time EHR connectivity, production deployment ✨ 🏥
Additional packages (components, document stores and the likes) to extend the capabilities of Haystack
Kubernetes-friendly ML model management, deployment, and serving.
📚 All of my recommendations for aspiring engineers in a single place, coming from various areas of interest.
The Best TypeScript framework for fine-tuning
Universal Python SDK to run AI workloads on Kubernetes
User documentation for KServe.
AI-ML Companion: an interactive platform to learn AI & ML by watching it work - 22 tracks, 300+ modules, live visualizations - plus 10 end-to-end portfolio proj…
A comprehensive platform for managing, testing, and leveraging Ollama AI models with advanced features for customization, workflow automation, and collaborative…
🧯 Kubernetes coverage for fault awareness and recovery, works for any LLMOps, MLOps, AI workloads.
45+ production-ready tutorials on data science, MLOps, and AI tools. All code is executable and adaptable for real projects.
A design-of-experiments platform for evaluating compound AI systems - find which technique drives quality, by how much, and whether the difference is real.
Plug-and-play, dependency-free web command center for DGX Spark fleets (and any GPU boxes): live per-node GPU/CPU/mem/temps/power, optional RouterOS switch moni…
Airbnb price prediction for Berlin using an end-to-end ML pipeline with data cleaning, scikit-learn model training, and a FastAPI prediction service packaged fo…