python-recsys VS xgboost

Compare python-recsys vs xgboost and see what are their differences.

python-recsys

A python library for implementing a recommender system (by ocelma)

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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python-recsys xgboost
0 10
1,468 25,438
- 0.7%
0.0 9.7
about 3 years ago 7 days ago
Python C++
http://www.gnu.org/copyleft/gpl.html 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.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.

python-recsys

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

We haven't tracked posts mentioning python-recsys 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 2023-05-09.
  • PSA: You don't need fancy stuff to do good work.
    10 projects | /r/datascience | 9 May 2023
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive documentation and community support, making it easy to learn and apply new techniques without needing specialized training or expensive software licenses.
  • xgboost VS CXXGraph - a user suggested alternative
    2 projects | 28 Feb 2022

What are some alternatives?

When comparing python-recsys 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

Surprise - A Python scikit for building and analyzing recommender systems

mlpack - mlpack: a fast, header-only C++ machine learning library

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.

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

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

Simple GAN - Attempt at implementation of a simple GAN using Keras

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.