khuyentran1401 / Machine-learning-pipelineLinks
Example machine learning pipeline with MLflow and Hydra
☆89Updated 2 years ago
Alternatives and similar repositories for Machine-learning-pipeline
Users that are interested in Machine-learning-pipeline are comparing it to the libraries listed below
Sorting:
- Demo for CI/CD in a machine learning project☆106Updated last year
- An end-to-end project on customer segmentation☆81Updated 2 years ago
- Practical Deep Learning at Scale with MLFlow, published by Packt☆160Updated last year
- Production-Ready Applied Deep Learning☆90Updated last year
- Demo for Using GitHub Actions in MLOps☆40Updated 2 years ago
- Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases wit…☆48Updated 3 years ago
- Serving TensorFlow models with TensorFlow Serving☆44Updated 3 years ago
- ☆65Updated last month
- Machine Learning Engineering with MLflow, published by Packt☆115Updated 11 months ago
- ☆38Updated 2 years ago
- Learn how to create reliable ML systems by testing code, data and models.☆87Updated 2 years ago
- A hands-on case study for demonstrating the stages involved in a machine learning project, from EDA to production.☆37Updated last year
- ☆31Updated 2 years ago
- Code samples for the Effective Data Science Infrastructure book☆115Updated 2 years ago
- A simple guide to MLOps through ZenML and its various integrations.☆187Updated last year
- ☆150Updated 3 years ago
- MLOps hands-on notes, notebooks and scripts of months of learning☆27Updated 2 years ago
- Introduction to MLflow with a demo locally and how to set it on AWS☆42Updated 4 years ago
- Partly lecture and partly a hands-on tutorial and workshop, this is a three part series on how to get started with MLflow. In this three …☆238Updated 4 years ago
- 🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.☆183Updated 10 months ago
- Curriculum and roadmap from 0 to Mastery for MLOps. Adding value to your machine learning model by deploying it for people to use it to s…☆183Updated 3 years ago
- 🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.☆264Updated 2 years ago
- Learn how to monitor ML systems to identify and mitigate sources of drift before model performance decay.☆86Updated 2 years ago
- ☆44Updated 2 years ago
- 100 applications built with H2O Wave☆98Updated 2 years ago
- Tutorials on creating a reproducible and maintainable data science project☆144Updated 2 years ago
- 🛠 Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.☆147Updated last year
- Best practices for engineering ML pipelines.☆35Updated 2 years ago
- In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits☆106Updated 3 years ago
- Example project with a CNN to train a Pokémon type classifier, adapted for DTC workshop☆35Updated last year