neptune-contrib VS xgboost

Compare neptune-contrib vs xgboost and see what are their differences.

xgboost

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 (by dmlc)
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neptune-contrib xgboost
0 5
26 23,205
- 0.9%
1.0 9.6
12 months ago 5 days ago
Python C++
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

neptune-contrib

Posts with mentions or reviews of neptune-contrib. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning neptune-contrib yet.
Tracking mentions began in Dec 2020.

xgboost

Posts with mentions or reviews of xgboost. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-28.

What are some alternatives?

When comparing neptune-contrib and xgboost you can also consider the following projects:

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

MLP Classifier - A handwritten multilayer perceptron classifer using numpy.

tensorflow - An Open Source Machine Learning Framework for Everyone

Keras - Deep Learning for humans

catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

mlpack - mlpack: a scalable C++ machine learning library --

LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.

scikit-learn - scikit-learn: machine learning in Python

MLflow - Open source platform for the machine learning lifecycle

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

vowpal_wabbit - Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)