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XGBoost

Appears in 11 awesome lists

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow. [Apache2]

Open github.comdmlc/xgboost

Found in these lists

Awesome C++

Section: Machine Learning · Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow. [Apache2]

FreshScore 94

Awesome Data Analysis

Section: Tools · Optimized distributed gradient boosting library for tree-based models.

FreshScore 80

AWESOME DATA SCIENCE

Section: General Machine Learning Packages

FreshScore 92

Awesome LLMOps

Section: Frameworks for Training · Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library.

ActiveScore 75

Awesome Machine Learning

Section: C++ · A parallelized optimized general purpose gradient boosting library.

FreshScore 93

Awesome Open Source AI

Section: 1. Core Frameworks & Libraries · Scalable, high-performance gradient boosting library. Still dominates Kaggle and tabular competitions.

FreshScore 89

Awesome Production Machine Learning

Section: Computation and Communication Optimisation · XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable.

FreshScore 92

Awesome Python

Section: Machine Learning · A scalable, portable, and distributed gradient boosting library.

FreshScore 94

Awesome Python Data Science

Section: Gradient Boosting · Scalable, Portable, and Distributed Gradient Boosting.

ActiveScore 71

Awesome Machine Learning with Ruby

Section: Related Resources

StaleScore 54

awesome-cpp

Section: Machine Learning Frameworks · Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

FreshScore 79

TensorFlow

How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post Accelerating TensorFlow Lite on Qualcomm Hexagon DSPs.

In 23 listsDetails

m2cgen

Transpile trained ML models into other languages. sklearn-porter - Transpile trained scikit-learn estimators to C, Java, JavaScript and others. mlflow - Manage the machine learning lifecycle, including experimentation, reproducibility and deployment. skll - Command-line utilities to make it easier…

In 16 listsDetails

PyTorch

(label: good first issue) PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.

In 16 listsDetails

transformers

(formerly known as pytorch-transformers and pytorch-pretrained-bert) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in…

In 14 listsDetails

TensorFlow-Slim

Official TensorFlow repository of state-of-the-art (SOTA) models and modeling solutions. Contains reference implementations for BERT, ResNet, Transformer, and many more with pre-trained weights and training scripts. Apache 2.0 licensed.

In 12 listsDetails

scikit-learn

Scikit-learn is a powerful machine learning library that provides a wide variety of modules for data access, data preparation and statistical model building.

In 10 listsDetails

CatBoost

General purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.

In 10 listsDetails

Caffe

is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.

In 10 listsDetails