stephabauva / ML_with_DAGsLinks
Get introduced to Directed Acyclic Graphs (DAGs) through Dagster with a simple ML program
☆12Updated 2 years ago
Alternatives and similar repositories for ML_with_DAGs
Users that are interested in ML_with_DAGs are comparing it to the libraries listed below
Sorting:
- A scikit-learn compatible estimator based on business-rules with interactive dashboard included☆28Updated 3 years ago
- Demo on how to use Prefect with Docker☆25Updated 2 years ago
- Build your feature store with macros right within your dbt repository☆38Updated 2 years ago
- A repository containing an introduction to Panel made to be support videos and talks.☆56Updated 3 years ago
- Building an API with the FastAPI framework to serve a scikit-learn model.☆18Updated 6 years ago
- Blog post on ETL pipelines with Airflow☆23Updated 5 years ago
- ☆29Updated last year
- A Python package to build predictive linear and logistic regression models focused on performance and interpretation☆30Updated last year
- dagster scikit-learn pipeline example.☆43Updated 2 years ago
- ☆41Updated 11 months ago
- Data Scientist code test☆19Updated 4 years ago
- Comparing Polars to Pandas and a small introduction☆44Updated 4 years ago
- ☆22Updated 9 months ago
- Build elegant dashboards and deploy with ease☆39Updated 9 months ago
- Automatically export Jupyter notebooks to various file formats (.py, .html, and more) on save.☆77Updated last year
- An automation tool to refactor Jupyter Notebooks to Python modules, with code dependency analysis.☆12Updated 3 months ago
- How to do data science with Optimus, Spark and Python.☆19Updated 5 years ago
- Sample projects using Ploomber.☆86Updated last year
- Collection of code snippets and utilities for streamlit apps☆22Updated 5 years ago
- Interactive cleaning for Pandas DataFrames☆15Updated 5 years ago
- Powerful rapid automatic EDA and feature engineering library with a very easy to use API 🌟☆53Updated 3 years ago
- Prune your sklearn models☆19Updated 7 months ago
- Predict the poverty of households in Costa Rica using automated feature engineering.☆23Updated 4 years ago
- PyCon Talks 2022 by Antoine Toubhans☆23Updated 2 years ago
- Investigation for PyDataLondon 2023 and ODSC 2023 conference comparing Pandas 2, Polars and Dask☆11Updated last year
- An abstraction layer for parameter tuning☆35Updated 9 months ago
- ☆24Updated 2 months ago
- ☆20Updated 3 years ago
- Instant search for and access to many datasets in Pyspark.☆34Updated 2 years ago
- Tools for working with Pandas, Plotly, and Dash.☆26Updated last year