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A curated list of awesome open source tools and commercial products for ML Experiment Tracking and Management ๐
MLOps for deploying a Credit Risk model
A simple app to help you find relevant machine learning papers to read.
An end to end ML project. Using MLflow for experiment tracking and model registry. Prefect for workflow orchestration. S3 for artifacts storage. AWS Lambda/ ECR for serverless model serving. AWS REST API gateway as endpoint to lambda function. GitHub Actions for CI/CD.
Hopsworks Machine Learning Api ๐ Model management with a model registry and model serving
Part of the Hydrosphere.io project.
Newron is a data-centric ML platform to easily build, manage, deploy and continuously improve models through data driven development.
Experiment tracking and model registry in the images segmentation project
Basic MLPlatform includes Model Registry and Inference Server
Experiment tracking and model registry in the NLP project
Built an E2E MLFlow Pipeline & hosted on AWS.
Advanced Machine Learning Regression: Predicting Car Prices
Go SDK to interact with the Hopsworks API
Logo Recognition App MLOps
Model Registry is the service that exposes API to save, fetch and delete machine learning models
Registration of pre-trained models found on Hugging Face using blockchain technology
To be used for Studio test cases only.
Example repo that showcase monorepo scenario. `cv` folder has an image segmentation model, and `nlp` folder has a text classification model. Load this repo as project in https://studio.iterative.ai to see models registered within a model registry.
List of model registry resources and tools
Tabular data experiment tracking with Neptune
Successfully developed a machine learning model to predict Airline Passenger Satisfaction by building an end-to-end MLOps pipeline. It integrates DVC for data versioning, a Dockerfile for containerization, and CI/CD using GitHub Actions for automated deployment.