The Best Gensim Alternatives in 2026

This repository provides semantic segmentation models with more than 500 pretrained convolutional and transformer backbones.

GPyTorch provides an efficient implementation of Gaussian processes using PyTorch.

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

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

A python library for accurate and scalable fuzzy matching, record deduplication and entity-resolution.

An open source Python library for drift detection in machine learning systems.

The lightly Python library supports self supervised learning on images.

PyCaret provides a low code AutoML platform for Python, with a scikit-learn native engine and React control plane.

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media.

nilearn provides Python tools for machine learning and neuroimaging analysis.

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

Python package which helps to debug machine learning classifiers and explain their predictions.

modAL provides a modular active learning framework for Python built on top of scikit-learn.

Spektral provides a Python framework for creating graph neural networks with Keras and TensorFlow.

Prophet provides forecasting procedures in R and Python that data scientists can tune.

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

Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.

FastDatasets helps create training datasets for large language models.

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

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

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

AIF360 provides fairness metrics and explanations for datasets and models, along with algorithms to mitigate bias.

This repository provides segmentation models with pretrained backbones for Keras and TensorFlow Keras.

LLMeBench provides a flexible framework for benchmarking large language models.