machinelearningnuremberg/DeepPipe

[KDD 2023] Deep Pipeline Embeddings for AutoML

37
/ 100
Emerging

This project helps machine learning engineers efficiently find the best machine learning pipeline for their tabular data. You input your dataset (like a pandas DataFrame), and it automatically searches for and outputs an optimized pipeline that provides the best predictive accuracy for your specific task. It's designed for data scientists and ML practitioners who build predictive models.

No commits in the last 6 months.

Use this if you want to quickly discover a high-performing machine learning model and its configuration for your tabular data without extensive manual experimentation.

Not ideal if you need fine-grained control over every aspect of your model architecture or are working with non-tabular data types like images or text.

predictive-modeling data-science-workflow model-optimization tabular-data-analysis machine-learning-engineering
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 13 / 25

How are scores calculated?

Stars

17

Forks

3

Language

Python

License

BSD-3-Clause

Last pushed

Jul 01, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/machinelearningnuremberg/DeepPipe"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.