Klalena / AWS-Serverless-Data-Engineering-PipelineLinks
This is a repository for the Duke University Cloud Computing course project on Serveless Data Engineering Pipeline. For this project, I recreated the below pipeline.
☆20Updated 4 years ago
Alternatives and similar repositories for AWS-Serverless-Data-Engineering-Pipeline
Users that are interested in AWS-Serverless-Data-Engineering-Pipeline are comparing it to the libraries listed below
Sorting:
- Best practices for engineering ML pipelines.☆36Updated 3 years ago
- ☆18Updated 4 years ago
- A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.☆37Updated 4 years ago
- Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.☆40Updated 11 months ago
- Build and deploy a serverless data pipeline on AWS with no effort.☆111Updated 2 years ago
- An example MLFlow project☆49Updated 11 months ago
- Deployment of ML models with AWS Lambda, ECR, Docker, and GitOps☆25Updated last week
- End to end MLRun demos☆93Updated last month
- This sample demonstrates how to setup an Amazon SageMaker MLOps end-to-end pipeline for Drift detection☆64Updated 2 years ago
- Materials for my 2021 NYU class on NLP and ML Systems (Master of Engineering).☆97Updated 3 years ago
- ☆28Updated 3 years ago
- ∞ Priceloop Engineering Conventions for Scala, Python, Git Workflow etc☆100Updated 3 years ago
- [Video]AWS Certified Machine Learning-Specialty (ML-S) Guide☆121Updated 11 months ago
- 🛠 Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.☆151Updated last year
- Capturing model drift and handling its response - Example webinar☆108Updated 6 years ago
- Learn how to monitor ML systems to identify and mitigate sources of drift before model performance decay.☆92Updated 3 years ago
- Scaling Python Machine Learning☆52Updated 2 years ago
- 🐍 Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projects☆82Updated 3 years ago
- Code samples for the Effective Data Science Infrastructure book☆116Updated 2 years ago
- A tool to deploy a mostly serverless MLflow tracking server on a GCP project with one command☆72Updated 7 months ago
- ☆21Updated 2 years ago
- demo CI/CD pipeline using MLRun, Kubeflow and GitHub Actions☆51Updated 3 years ago
- 🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.☆184Updated last year
- ☆66Updated 7 months ago
- Using a feature store to connect the DataOps and MLOps workflows to enable collaborative teams to develop efficiently.☆56Updated 3 years ago
- A tutorial that helps Big Data Engineers ramp up faster by getting familiar with PySpark dataframes and functions. It also covers topics …☆20Updated 4 years ago
- [Course-2020-2023] taught at Duke MIDS. This is also a Coursera Course that covers MLOps, ML Engineering and the foundations of Cloud Co…☆141Updated 11 months ago
- Operations Research Algorithms☆19Updated last year
- Repository with sample code and instructions for "Continuous Intelligence" and "Continuous Delivery for Machine Learning: CD4ML" workshop…☆142Updated last year
- Example templates for the delivery of custom ML solutions to production so you can get started quickly without having to make too many de…☆74Updated last year