awesome-repositories.com
Blog
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectAboutHow we rankPressMCP server
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
Back to scikit-learn-contrib/deslib

Open-source alternatives to DESlib

10 open-source projects similar to scikit-learn-contrib/deslib, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best DESlib alternative.

  • devamoghs/machine-learning-with-pythondevAmoghS avatar

    devAmoghS/Machine-Learning-with-Python

    1,333View on GitHub↗

    This repository serves as an educational collection of practical examples and tutorials designed to facilitate the study of machine learning and data science concepts using Python. It provides a structured environment for learning core algorithms and data analysis techniques through hands-on implementation and iterative exploration. The project covers a broad range of analytical capabilities, including predictive modeling for regression, classification, and clustering tasks, as well as network topology analysis for identifying influence patterns in interconnected data. It also incorporates na

    Pythonbeginner-friendlydata-sciencedeep-learning
    View on GitHub↗1,333
  • dswah/pygamdswah avatar

    dswah/pyGAM

    1,005View on GitHub↗

    CONTRIBUTORS WELCOME Generalized Additive Models in Python

    Python
    View on GitHub↗1,005
  • kevinmusgrave/pytorch-metric-learningKevinMusgrave avatar

    KevinMusgrave/pytorch-metric-learning

    6,328View on GitHub↗

    PyTorch Metric Learning is an open-source library for training neural networks to produce similarity-preserving embedding spaces. It provides a modular framework where interchangeable loss functions, mining strategies, and evaluation tools can be composed to learn representations that map similar items to nearby points and dissimilar items to distant points in the embedding space. The library distinguishes itself through a highly configurable architecture that separates concerns across several interchangeable components. Users can assemble custom loss functions from pluggable distance metrics

    Pythoncomputer-visioncontrastive-learningdeep-learning
    View on GitHub↗6,328

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Find more with AI search
  • koaning/human-learnK

    koaning/human-learn

    0View on GitHub↗
    View on GitHub↗0
  • madeleineudell/lowrankmodels.jlM

    madeleineudell/LowRankModels.jl

    0View on GitHub↗
    View on GitHub↗0
  • scikit-learn-contrib/mapiescikit-learn-contrib avatar

    scikit-learn-contrib/MAPIE

    1,519View on GitHub↗

    .. -- mode: rst --

    Jupyter Notebookclassificationconfidence-intervalsconformal-prediction
    View on GitHub↗1,519
  • scikit-learn-contrib/metric-learnscikit-learn-contrib avatar

    scikit-learn-contrib/metric-learn

    1,436View on GitHub↗

    Metric learning algorithms in Python

    Python
    View on GitHub↗1,436
  • scikit-learn-contrib/py-earthS

    scikit-learn-contrib/py-earth

    0View on GitHub↗
    View on GitHub↗0
  • scikit-multilearn/scikit-multilearnscikit-multilearn avatar

    scikit-multilearn/scikit-multilearn

    953View on GitHub↗

    A scikit-learn based module for multi-label et. al. classification

    Python
    View on GitHub↗953
  • tensorflow/similaritytensorflow avatar

    tensorflow/similarity

    1,025View on GitHub↗

    TensorFlow Similarity is a Python framework designed for training neural networks to learn high-dimensional vector representations and perform similarity-based retrieval. It provides a comprehensive toolkit for metric learning, enabling the development of systems that group similar items together in vector space and identify them through distance-based comparisons. The library distinguishes itself by integrating specialized training techniques, such as contrastive and triplet-based learning, with robust data management tools that ensure stable model convergence. It supports self-supervised re

    Pythonbarlow-twinsclusteringcontrastive-learning
    View on GitHub↗1,025