Topics / #gradient-boosting

Gradient-boosting projects on GitHub

Gradient boosted tree algorithms for tabular machine learning.

As of , the most-starred Gradient-boosting projects on GitHub are shap (25.8K stars), machine-learning-for-trading (21.4K stars) and LightGBM (18.9K stars). GitHub.Locker tracks 6 Gradient-boosting repositories with 103.6K stars combined. The fastest-growing on October 16 was machine-learning-for-trading, with +16 stars in a day.

6Projects
103.6KStars in total
+23Stars in a day
Browse in the catalog →github.com/topics/gradient-boosting ↗

Hot right now

Most stars gained in a day · Oct 16

+16

machine-learning-for-trading

stefan-jansen/machine-learning-for-trading · ★ 21.4K

The code repository for Machine Learning for Trading, 3rd Edition by Stefan Jansen: an end-to-end workflow for building, testing, and deploying ML-driven trading strategies, from data sourcing to live execution.

+4

LightGBM

lightgbm-org/LightGBM · ★ 18.9K

LightGBM is a gradient boosting framework that uses tree-based learning algorithms, used for ranking, classification and many other machine learning tasks.

+2

shap

shap/shap · ★ 25.8K

SHAP is a Python library that explains the output of any machine learning model using Shapley values from game theory — it tells you how much each feature contributed to a given prediction.

+1

MLAlgorithms

rushter/MLAlgorithms · ★ 11.2K

A collection of minimal, clean Python implementations of core machine learning algorithms, built so people can learn how the algorithms actually work internally.

The all-time top

6 projects · by stars

  1. #1 · shap/shap

    shap

    SHAP is a Python library that explains the output of any machine learning model using Shapley values from game theory — it tells you how much each feature contributed to a given prediction.

    25.8K
  2. #2 · stefan-jansen/machine-learning-for-trading

    machine-learning-for-trading

    The code repository for Machine Learning for Trading, 3rd Edition by Stefan Jansen: an end-to-end workflow for building, testing, and deploying ML-driven trading strategies, from data sourcing to live execution.

    21.4K
  3. #3 · lightgbm-org/LightGBM

    LightGBM

    LightGBM is a gradient boosting framework that uses tree-based learning algorithms, used for ranking, classification and many other machine learning tasks.

    18.9K
  1. 4

    numpy-ml

    16.3Kddbourgin/numpy-ml · Python

    A collection of machine learning algorithms — Gaussian mixture models, HMMs, neural networks, tree ensembles, reinforcement learning agents and more — implemented from scratch in pure NumPy.

  2. 5

    MLAlgorithms

    11.2Krushter/MLAlgorithms · Python

    A collection of minimal, clean Python implementations of core machine learning algorithms, built so people can learn how the algorithms actually work internally.

  3. 6

    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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