Topics / #hyperparameter-optimization

Hyperparameter-optimization projects on GitHub

Automated search for optimal machine learning hyperparameters.

As of , the most-starred Hyperparameter-optimization projects on GitHub are ray (44.1K stars), d2l-en (29.9K stars) and optuna (14.9K stars). GitHub.Locker tracks 7 Hyperparameter-optimization repositories with 135.4K stars combined. The fastest-growing on October 17 was d2l-en, with +13 stars in a day.

7Projects
135.4KStars in total
+31Stars in a day
Browse in the catalog →github.com/topics/hyperparameter-optimization ↗

Hot right now

Most stars gained in a day · Oct 17

+13

d2l-en

d2l-ai/d2l-en · ★ 29.9K

An interactive open-source deep learning book that teaches concepts, context, and runnable code together, with examples in multiple frameworks. Its premise: the best way to understand deep learning is learning by doing.

+10

ray

ray-project/ray · ★ 44.1K

Ray is an open-source framework for scaling AI and Python applications: a core distributed runtime plus a set of AI libraries that simplify ML compute.

+3

autogluon

autogluon/autogluon · ★ 10.8K

AutoGluon is an open-source Python library that automates machine learning: feed it your data and it delivers strong predictive performance in about three lines of code.

+2

optuna

optuna/optuna · ★ 14.9K

Optuna is an open-source framework for automatic hyperparameter optimization, built primarily for machine learning: you wrap your training code in an objective function and it searches for the best settings automatically.

The all-time top

7 projects · by stars

  1. #1 · ray-project/ray

    ray

    Ray is an open-source framework for scaling AI and Python applications: a core distributed runtime plus a set of AI libraries that simplify ML compute.

    44.1K
  2. #2 · d2l-ai/d2l-en

    d2l-en

    An interactive open-source deep learning book that teaches concepts, context, and runnable code together, with examples in multiple frameworks. Its premise: the best way to understand deep learning is learning by doing.

    29.9K
  3. #3 · optuna/optuna

    optuna

    Optuna is an open-source framework for automatic hyperparameter optimization, built primarily for machine learning: you wrap your training code in an objective function and it searches for the best settings automatically.

    14.9K
  1. 4

    nni

    14.4Kmicrosoft/nni · Python

    NNI (Neural Network Intelligence) is Microsoft's open-source AutoML toolkit that automates the machine learning lifecycle: feature engineering, neural architecture search, model compression, and hyperparameter tuning.

  2. 5

    wandb

    11.3Kwandb/wandb · Python

    wandb is the Weights & Biases AI developer platform: a Python library and hosted service for tracking, visualizing, and managing machine learning experiments from datasets to production models, including LLM apps via its Weave toolset.

  3. 6

    autogluon

    10.8Kautogluon/autogluon · Python

    AutoGluon is an open-source Python library that automates machine learning: feed it your data and it delivers strong predictive performance in about three lines of code.

  4. 7

    tpot

    10.1KEpistasisLab/tpot · Jupyter Notebook

    TPOT, the Tree-based Pipeline Optimization Tool, is a Python AutoML library that uses genetic programming to automatically optimize machine learning pipelines for your data; the README calls it your Data Science Assistant.

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