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pytorch tabular provides a unified framework for deep learning models on tabular data.

PyTorch Frame provides a library for applying deep learning models to tabular data.

This TabGAN repository reviews research on applying GANs to generate tabular data.

Apache Spark is a unified engine for large-scale data processing and analytics.

Adala automates data labeling through an autonomous agent framework for organizing labeled datasets.

tsfresh automatically extracts relevant features from time series data.

Snorkel helps generate training data programmatically through weak supervision.

ADAM analyzes genomics data with specialized file formats built on Apache Spark, Avro, and Parquet.

Modin scales Pandas data workflows by changing a single line of code in a project.

DB-GPT is an open-source agentic data assistant for AI and data products.

Feature Engine provides Python tools for feature engineering and selection that are compatible with scikit-learn.

Giskard provides open source evaluation and testing tools for LLM agents.

Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

NALP covers Natural Adversarial Language Processing through a dedicated library.

neuropredict evaluates predictive performance using neuroimaging features.

Cornac provides a framework for comparing multimodal recommender systems and recommendation algorithms.

Open-RAG-Eval evaluates retrieval-augmented generation without requiring golden answers.

nilearn provides Python tools for machine learning and neuroimaging analysis.

This repository implements YOLOv3 variants in PyTorch for real time object detection, training, validation, inference, and export.

Captum explains model behavior and supports interpretability analysis for PyTorch systems.

AutoViz automatically creates visualizations for datasets of different sizes from a single line of code.

A Python package to assess and improve fairness of machine learning models.

WhichLLM tests local language models on a user’s hardware and ranks them using recent benchmarks.

The Featuretools Python library supports automated feature engineering and is published as open source.