GitHub topics: ml-ops

Repositories

upgundecha/howtheysre

A curated collection of publicly available resources on how technology and tech-savvy organizations around the world practice Site Reliability Engineering (SRE)

Language: JavaScript - Size: 547 KB - Last synced at: 41 minutes ago - Pushed at: 3 months ago - Stars: 9,308 - Forks: 814

theNewFlesh/flatiron

Standardized computer vision pipeline framework with a chainable API and procedurally defined model architecture

Language: Python - Size: 33.2 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 2 - Forks: 0

EthicalML/awesome-production-machine-learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

Size: 2.36 MB - Last synced at: 5 days ago - Pushed at: 8 days ago - Stars: 18,412 - Forks: 2,342

PrefectHQ/prefect

Prefect is a workflow orchestration framework for building resilient data pipelines in Python.

Language: Python - Size: 172 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 19,177 - Forks: 1,813

SE-ML/awesome-seml

A curated list of articles that cover the software engineering best practices for building machine learning applications.

Size: 248 KB - Last synced at: 4 days ago - Pushed at: about 1 year ago - Stars: 1,278 - Forks: 124

sematic-ai/sematic

An open-source ML pipeline development platform

Language: Python - Size: 20.2 MB - Last synced at: about 6 hours ago - Pushed at: 4 months ago - Stars: 990 - Forks: 63

zsxkib/cog-template

Template for Cog models with built-in model weights caching and CDN integration

Language: Python - Size: 11.7 KB - Last synced at: 6 days ago - Pushed at: 27 days ago - Stars: 1 - Forks: 0

vortico/flama

Fire up your models with the flame 🔥

Language: Python - Size: 6.53 MB - Last synced at: 1 day ago - Pushed at: about 1 month ago - Stars: 277 - Forks: 15

MatsMoll/aligned

The DBT of ML, as Aligned describes data dependencies in ML systems, and reduce technical data debt

Language: Python - Size: 6.08 MB - Last synced at: 12 days ago - Pushed at: about 2 months ago - Stars: 58 - Forks: 2

realjules/monitor.ai

monitor.ai: Non-intrusive monitoring for FDA-approved medical AI, helping healthcare organizations ensure safety and compliance without modifying validated models.

Language: Jupyter Notebook - Size: 163 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

sayande01/AI-Architect-Playbook

25-day journey to master AI consulting! This repo features Jupyter notebooks covering AI architecture, ML, generative AI, cloud deployments, and MLOps to build your skills & portfolio.

Language: Jupyter Notebook - Size: 10.7 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

Azure-Samples/azure-databricks-mlops-mlflow

Azure Databricks MLOps sample for Python based source code using MLflow without using MLflow Project.

Language: Jupyter Notebook - Size: 3.2 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 84 - Forks: 53

wahidpanda/End-to-End_MLOPS_GitHub_workflows_with_DockerHub

Create an End-to-End MLops project with GitHub action workflow and DockerHub integration.

Language: Python - Size: 14.6 KB - Last synced at: about 1 month ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

chalk-ai/examples

Curated examples and patterns for using Chalk. Use these to build your feature pipelines.

Language: Python - Size: 832 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 11 - Forks: 1

mituskillologies/mlops-mitadt-dec24

Programs conducted at MIT ADT University, Pune in FDP on MLOps Essentials during December 2024.

Language: Jupyter Notebook - Size: 143 KB - Last synced at: about 2 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

Blacksujit/Location-Based-Analysis

This project aims to perform restaurant location-based analysis using machine learning techniques. It involves predicting restaurant ratings based on user inputs and displaying restaurant locations on a map.

Language: HTML - Size: 81 MB - Last synced at: about 2 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

uday160386/ml-model-as-rest-api

A simple example on how to provide ML model (DecissionTreeClassifier) as a REST Service. The app is containerize and deployed in Azure Cloud

Language: Python - Size: 89.3 MB - Last synced at: 2 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

vortico/flama-demos

Examples showcasing Flama 🔥

Language: Python - Size: 1.42 MB - Last synced at: 12 days ago - Pushed at: 6 months ago - Stars: 2 - Forks: 0

guidelabs/infembed

Find the samples, in the test data, on which your (generative) model makes mistakes.

Language: Python - Size: 4.73 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 25 - Forks: 1

terilios/automated_data_scientist

Automated Data Scientist: An intelligent, adaptive data analysis tool that leverages AI-driven automation to dynamically plan, execute, and refine data science workflows. Automatically handles data preparation, analysis planning, code generation, and result interpretation using advanced language models.

Language: Python - Size: 207 KB - Last synced at: 2 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 1

chenjoshua7/chen_musicbox

NLP web app for genre classification using a DistilBERT model. Developed and containerized with Docker, deployed on Azure for scalable real-time predictions. Includes automated data logging to Azure Blob Storage for seamless model evaluation, feedback, and retraining. Fully production-ready with robust MLOps integration.

Language: Jupyter Notebook - Size: 137 KB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

a-ngo/ml-ops

These are my personal notes regarding Machine Learning DevOps stuff

Language: Jupyter Notebook - Size: 18.8 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

nikofebrianur/French-Twitter-Sentiment-Analysis

This machine learning pipeline project aims to develop an ML model to identify customer sentiment from French-language tweets on social media.

Language: Jupyter Notebook - Size: 320 KB - Last synced at: 5 days ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

NucleusEngineering/hack-your-pipe

Efficient streaming data ingestion, transformation & activation

Language: Python - Size: 3.01 MB - Last synced at: 10 months ago - Pushed at: about 2 years ago - Stars: 28 - Forks: 3

gagan-iitb/ComputerSysDesign

Designing IT and ML Applications using Systems Thinking Approach at IIT Bhilai (CS559)

Size: 4 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 18 - Forks: 3

MGTheTrain/ml-ops-ftw 📦

Repository showcasing ML Ops practices with kubeflow and mlflow

Language: HCL - Size: 1.69 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

gasparian/ml-serving-template

Serving large ml models independently and asynchronously via message queue and kv-storage for communication with other services [EXPERIMENT]

Language: Python - Size: 558 KB - Last synced at: 20 days ago - Pushed at: almost 4 years ago - Stars: 15 - Forks: 1

jgvaraujo/ml-deployment-on-gcloud

A pipeline to CI/CD of a machine learning model on Google Cloud Run

Language: Python - Size: 2.32 MB - Last synced at: 10 months ago - Pushed at: about 2 years ago - Stars: 31 - Forks: 7

nikofebrianur/Bank-Customer-Churn-Prediction

This machine learning pipeline project aims to develop an ML model to identify bank customer churn.

Language: Jupyter Notebook - Size: 1.87 MB - Last synced at: 5 days ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

haddagart/awesome-ml-bookmarks

[Under construction] A list of interesting bookmarks, blogs, channels, papers, and anything that can be considered as a day to day reference for an AI, DS, ML, or DL practioner.

Size: 6.84 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

aws-samples/amazon-sagemaker-pipeline-deploy-manage-100x-models-python-cdk

This GitHub repository showcases the implementation of a comprehensive end-to-end MLOps pipeline using Amazon SageMaker pipelines to deploy and manage 100x machine learning models. The pipeline covers data pre-processing, model training/re-training, hyperparameter tuning, data quality check,model quality check, model registry, and model deployment.

Language: Python - Size: 1.59 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0