Chim-SO / cookiecutter-mlops
A logical, reasonably standardized, but flexible project structure for MLops.
☆35Updated 5 months ago
Alternatives and similar repositories for cookiecutter-mlops:
Users that are interested in cookiecutter-mlops are comparing it to the libraries listed below
- Tutorials on creating a reproducible and maintainable data science project☆143Updated 2 years ago
- Demo for CI/CD in a machine learning project☆104Updated last year
- Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in productio…☆80Updated last year
- Find data quality issues and clean your data in a single line of code with a Scikit-Learn compatible Transformer.☆130Updated last year
- summarytools in jupyter notebook☆105Updated 7 months ago
- Code repository for the online course "Feature Engineering for Time Series Forecasting".☆183Updated last year
- Applied Machine Learning Explainability Techniques, published by Packt☆243Updated last year
- Project bike sharing predictor☆75Updated 3 weeks ago
- Materials for the AI Dev 2024 conference workshop "Deploy and Monitor ML Pipelines with Python, Open Source, and Free Applications"☆93Updated this week
- Template for a data science project☆710Updated 3 months ago
- A book of subtle code tricks and gem resources for all things data, machine learning and deep learning.☆165Updated 6 months ago
- Une liste de ressources sur tout ce qui touche à la prise de décision : vidéos, tutoriels, livres, documents, thèses, articles, datasets …☆9Updated 7 months ago
- Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications☆103Updated last year
- Slides for "Feature engineering for time series forecasting" talk☆58Updated 2 years ago
- An end-to-end project on customer segmentation☆81Updated 2 years ago
- pipreqs with jupyter notebook support☆68Updated last year
- ☆48Updated 7 months ago
- Machine Learning for Imbalanced Data, published by Packt☆271Updated 2 months ago
- Practical Deep Learning at Scale with MLFlow, published by Packt☆159Updated last year
- This is an example project to understand how to work with Kedro and MLFlow for machine learning projects.☆12Updated 2 years ago
- 🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.☆262Updated 2 years ago
- ☆53Updated 7 months ago
- Learn how to create, develop, and maintain a state-of-the-art MLOps code base☆504Updated 2 weeks ago
- Feature engineering package with sklearn like functionality☆52Updated 7 months ago
- Machine Learning Engineering with MLflow, published by Packt☆115Updated 9 months ago
- Develop and deploy a real-time feature pipeline in Python, using Bytewax 🐝 and Hopsworks Feature Store.☆134Updated last year
- ☆278Updated last year
- Fetch, transform and plot real-time OHLC data from Coinbase using Bytewax, Bokeh and Streamlit☆127Updated 11 months ago
- Interpretable ML with Python, 2E - published by Packt☆93Updated last year
- ☆33Updated 2 months ago