hackalog / make_better_defaultsLinks
Improving your data science workflows with "make". A Pydata Global 2021 Talk
☆34Updated 3 years ago
Alternatives and similar repositories for make_better_defaults
Users that are interested in make_better_defaults are comparing it to the libraries listed below
Sorting:
- Code samples for the Effective Data Science Infrastructure book☆115Updated 2 years ago
- It's all in the name☆81Updated 2 years ago
- Explore and compare 1K+ accurate decision trees in your browser!☆169Updated last year
- Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases wit…☆49Updated 3 years ago
- Streamline scikit-learn model comparison.☆143Updated 2 years ago
- 🐍 Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projects☆82Updated 3 years ago
- 🛠 Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.☆149Updated last year
- ☆66Updated 5 months ago
- Tutorials on creating a reproducible and maintainable data science project☆149Updated 3 years ago
- A tutorial on how to use kedro-mlflow plugin (https://github.com/Galileo-Galilei/kedro-mlflow) to synchronize training and inference and …☆40Updated 3 years ago
- An example MLFlow project☆49Updated 9 months ago
- Start a data science project with modern tools☆202Updated 2 years ago
- Repo for Vizzu workshop materials.☆46Updated last year
- skops is a Python library helping you share your scikit-learn based models and put them in production☆500Updated last week
- 🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.☆183Updated last year
- Decorators that logs stats.☆115Updated 7 months ago
- pipreqs with jupyter notebook support☆70Updated 2 years ago
- A repository that showcases how you can use ZenML with Git☆70Updated 2 months ago
- Tutorials for Fugue - A unified interface for distributed computing. Fugue executes SQL, Python, and Pandas code on Spark and Dask withou…☆114Updated last year
- Super Simple Similarities Service☆154Updated 6 months ago
- Demo on how to use Prefect with Docker☆27Updated 3 years ago
- A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.☆37Updated 4 years ago
- Complementary code for blog posts☆24Updated 9 months ago
- Joining the modern data stack with the modern ML stack☆201Updated 2 years ago
- Sensible multi-core apply function for Pandas☆88Updated 3 weeks ago
- End-to-end deep learning on your desktop or server.☆105Updated last year
- This Repository contains the material for the tutorial "Introduction to MLOps with MLflow" held at pyData/pyCon Berlin 2022.☆22Updated 3 years ago
- An abstraction layer for parameter tuning☆35Updated last year
- A list of projects relying on Iterative.AI tools to achieve awesomeness☆67Updated last year
- Learn how to create reliable ML systems by testing code, data and models.☆89Updated 3 years ago