1.scikit-learn / scikit-learn
scikit-learn: machine learning in Python
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32 repositories by Attention Score · Oct 30, 2026 – Nov 5, 2026 (UTC)
scikit-learn: machine learning in Python
Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
Fast and memory-efficient exact attention
Datasets, Transforms and Models specific to Computer Vision
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
a generalist algorithm for cellular segmentation with human-in-the-loop capabilities
Module for statistical learning, with a particular emphasis on time-dependent modelling
Toolbox for the analysis of smFISH images.
An open source python library for automated feature engineering
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
StarDist - Object Detection with Star-convex Shapes
🌊 Online machine learning in Python
Python implementations of the Boruta all-relevant feature selection method.
Automated mapping of pedestrian networks from aerial imagery tiles
Speech recognition module for Python, supporting several engines and APIs, online and offline.
A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.)
Feature engineering and selection open-source Python library compatible with sklearn.
Genetic Programming in Python, with a scikit-learn inspired API
Dataflow compiler for QNN inference on FPGAs
Python library for working with Music Information Retrieval datasets
LAVIS - A One-stop Library for Language-Vision Intelligence
Automated Machine Learning with scikit-learn
A Python scikit for building and analyzing recommender systems
Fawkes, privacy preserving tool against facial recognition systems. More info at https://sandlab.cs.uchicago.edu/fawkes
Sequential model-based optimization with a `scipy.optimize` interface
A Flow-based Generative Network for Speech Synthesis
Transpile trained scikit-learn estimators and transformers to C, C#, Go, Java, JavaScript, PHP and Ruby.
Rumale is a machine learning library in Ruby
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
A tool for holistic analysis of language generations systems
MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction (Bioinformatics)
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