91 Open source projects that are alternatives of or similar to merlin

CartPole game by Reinforcement Learning, a journey from training to inference

A lightweight tool to get an AI Infrastructure Stack up in minutes not days. K3ai will take care of setup K8s for You, deploy the AI tool of your choice and even run your code on it.

A project-based course on the foundations of MLOps with a focus on intuition and application.

The MLOps Workload Orchestrator solution helps you streamline and enforce architecture best practices for machine learning (ML) model productionization. This solution is an extendable framework that provides a standard interface for managing ML pipelines for AWS ML services and third-party services.

MLOps Case Study

Engine for ML/Data tracking, visualization, dashboards, and model UI for Polyaxon.

Portable automation meta-framework to manage, describe, connect and reuse any artifacts, scripts, tools and workflows on any platform with any software and hardware in a non-intrusive way and with minimal effort. Try it using this tutorial to modularize and automate ML Systems benchmarking from the Student Cluster Competition at SC'22:

Serving TensorFlow models with TensorFlow Serving 📙

A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.

A set of demo of deploying a Machine Learning Model in production using various methods

A declarative KubeFlow Management Tool

[Machine Learning Engineer Basic Guide] 부스트캠프 AI Tech - Product Serving 자료

A generic template for building end-to-end machine learning projects

A tool for training models to Vertex on Google Cloud Platform.

GitHub Action that allows you to create or connect to your Azure Machine Learning Workspace.

Black-box optimization library

Lightweight and Fast Feature Store Powered by Go (and Rust).

A Collection of GitHub Actions That Facilitate MLOps

Docker images for fastai

This is an example of a Containerized Flask Application that can deploy to many target environments including: AWS, GCP and Azure.

The Fuzzy Labs guide to the universe of open source MLOps

Algorithm engineering is hard enough: don't spend your time with logistics. QA-Board organizes your runs and lets you visualize, compare and share results.

Operationalize a video anomaly detection model with Azure ML

Coarse-grained lineage and tracing for machine learning pipelines.

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

A collection of portable workflows, automation recipes and components for MLOps in a unified CK format. Note that this repository is outdated - please check the 2nd generation of the CK workflow automation meta-framework with portable MLOps and DevOps components here:

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All content related to machine learning from my blog

a simplified machine learning container platform that helps teams get started with an automated workflow

MLOps template with examples for Data pipelines, ML workflow management, API development and Monitoring.

GitHub Action that allows you to attach, create and scale Azure Machine Learning compute resources.

Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng

PyTorch Lightning + Hydra. A very user-friendly template for rapid and reproducible ML experimentation with best practices. ⚡🔥⚡

Combinator.ml's central repo, documentation and website

Helm charts for creating reproducible and maintainable deployments of Polyaxon with Kubernetes.

Crane is a easy-to-use and beautiful desktop application helps you build manage your container images.

The collaboration workspace for Machine Learning

The goal of this repository is to enable data scientists and ML engineers to develop data science use cases and making it ready for production use. This means focusing on the versioning, scalability, monitoring and engineering of the solution.

📒 Experiment tracking tool and model registry

Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.

Polyaxon Core Client & CLI to streamline MLOps

This repository provides AI/ML service(MachineLearning model serving) modernization solution using Amazon SageMaker, AWS CDK, and AWS Serverless services.

A GitHub Action that makes it easy to use Great Expectations to validate your data pipelines in your CI workflows.

GitHub Action that allows you to deploy machine learning models in Azure Machine Learning.

mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.

A collection of WhyLogs examples in various languages

Serving PyTorch models with TorchServe 🔥

Machine Learning Operator & Controller for Kubernetes

MONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.

Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

FuseML aims to provide an MLOps framework as the medium dynamically integrating together the AI/ML tools of your choice. It's an extensible tool built through collaboration, where Data Engineers and DevOps Engineers can come together and contribute with reusable integration code.

FakeFinder builds a modular framework for evaluating various deepfake detection models, offering a web application as well as API access for integration into existing workflows.

Evaluate wandb, tensorboard, neptune, mlflow, etc

A library for managing, validating, summarizing, and visualizing data.

All of my recommendations for aspiring engineers in a single place, coming from various areas of interest.

DataOps framework for Machine Learning projects.

A library for performing hyperparameter optimization

Extensible Python SDK for developing Flyte tasks and workflows. Simple to get started and learn and highly extensible.

Test Suites for Validating ML Models & Data. Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.

Completely Scalable FastAPI based template for Machine Learning, Deep Learning and any other software project which wants to use Fast API as an API framework.