etsi-ai/etna
A high level abstraction library designed for effortless tabular data based tasks.
This tool helps machine learning practitioners quickly train and evaluate neural network models on structured data, such as CSV files. You provide your tabular data, specify the target variable, and the tool outputs a trained model that can make predictions. It's ideal for data scientists, researchers, or anyone needing to rapidly prototype or deploy simple neural networks without deep technical complexity.
Use this if you need a fast, straightforward way to build and test neural network models on structured (tabular) datasets, especially for classification or regression tasks, with automatic data preparation.
Not ideal if you are working with unstructured data like images, text, or audio, or if you require highly custom, complex neural network architectures beyond simple sequential layers.
Stars
27
Forks
28
Language
Python
License
BSD-2-Clause
Category
Last pushed
Feb 25, 2026
Commits (30d)
0
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